How Social Network Influences the Growth of Entrepreneurial Enterprises: Perspective on Organizational and Personal Network

Huatao Peng; Bingbing Li; Yang Liu

doi:10.1177/21582440221108178

How Social Network Influences the Growth of Entrepreneurial Enterprises: Perspective on Organizational and Personal Network

Peng, Huatao; Li, Bingbing; Liu, Yang 2022-06-27 00:00:00 Network size, network density, and tie strength together determine the function of social network and affect the growth of entrepreneurial enterprises. However, how the role of network size, network density, and tie strength on the growth of entrepreneurial enterprises remains inconsistent, as well as the effect of organizational and personal network remains unclear. To solve these relationships, we employ meta-analysis to reach study goals by researching 31 independent samples from 28 references with 5,259 observations. Results have shown two main findings: (1) Both network size and tie strength have a positive and significant impact on the growth of entrepreneurial enterprises, while network density does not correlate with the growth. (2) Organizational network mainly plays a positive effect between network size and growth, while personal network plays a more significant role in the relationship of tie strength and growth than organizational network. These results promote managers to take productive strategies for entrepreneurial enterprises’ growth. Our study provides a meta-analysis to merge different sounds about the relationship of network properties to the growth of entrepreneurial enterprises, emphasizing moderators of organizational and personal networks among these above relationships. Thus, these findings make significant contributions to the field of entrepreneurship. Keywords social network, network size, network density, tie strength, organizational network, personal network, meta-analysis members, and it may offset the incremental benefits. While Introduction Ostgaard and Birley (1996) and Batjargal (2005b) obtained a Resources obtained from social network can assist entrepre- different result, network size negatively correlates with neurs to overcome difficulties, challenges, and even survival growth. As for network density, sparse networks helped iden- (Drummond et al., 2018). Social network provides low-cost, tify entrepreneurial opportunities to capture non-repetitive fast access to resources, including information technology, information (Bhagavatula et al., 2010; J. Yang & Zhang, financial capital, physical assets, etc. (Bratkovic et al., 2009; 2015) and increase the chances of creating competitive Cantner & Stützer, 2010; Hillman & Dalziel, 2003). Social advantages. However, dense network led to redundant infor- network also provides a convenient communication channel mation (Singh et al., 2000), limited its access to a wide range between entrepreneurial enterprises and external organiza- of information, and hindered its growth and progress. Whereas, tions for timely and valuable information (Diánez-González Bhagavatula and Elfring (2010) considered dense network & Camelo-Ordaz, 2019), achieving high growth and good increased mutual benefit between venture enterprises and performance (Ge et al., 2009). other members. Cantner and Stützer (2010) believed family However, some scholars hold different views on the role of social network. Not all social networks could generate posi- Wuhan University of Technology, China tive social capital. The key is how to excavate the properties Linköping University, Sweden of social network (Bratkovic et al., 2009). A larger network University of Vaasa, Finland made it more likely to provide rich information (Singh et al., Corresponding Author: 2000) and cooperate with its suppliers, customers, and com- Yang Liu, Department of Management and Engineering, Linköping petitors (Galkina & Lundgren-Henriksson, 2017). But Hansen University, SE-581 83 Linköping, Sweden. (1995) thought a larger network made less time to keep with Email: yang.liu@liu.se Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open or friends could help entrepreneurial enterprises increase the two dimensions of personal network and organizational net- chances of success and reduce their distrust because weak ties work. So we have provided six hypotheses, trying to build a led to arbitrage on potentially high-margin ideas (Bradley framework for network type, network properties, and the et al., 2012). Bhagavatula and Elfring (2010) held opposite growth of entrepreneurial enterprises. ideas. Weak ties could increase the possibility of obtaining The contributions of this paper consist of two points. more scarce resources, reduce the redundancy of information, Firstly, this paper enriches the literature and responds to the and enhance the chances of successful entrepreneurship. calls to research the relationships between network proper- Therefore, it would be inconsistent views about the influence ties and the growth of entrepreneurial enterprises at a greater of network properties-growth relationship. depth. Secondly, we have investigated the moderator of orga- So far, some scholars have used meta-analysis to research nizational and personal networks on the network properties- the effect of some network properties on firm performance, growth relationship. but further research still exists. Stam et al. (2014) focused on The structure of this paper is as follows: In Section 2, we small firms and selected control variables for firm type, review the theories of social network and the growth of industrial type, and economical type, and the variables are entrepreneurial enterprises. Section 3 presents the basic personal network’ structural holes, strong ties, weak ties, and hypotheses of the research. Section 4 introduces the method- diversity. Rauch et al. (2016) mainly researched network ology and analytical procedure. Section 5 discusses theoreti- cohesion and diversity with control variables as firm age, cal insights and managerial implications. Finally, Section 6 firm size, industry. However, the effectiveness of entrepre- presents limitations and suggestions for future research. neurs’ personal network to entrepreneurial performance is usually measured as organizational performance, neglecting Literature Review influences of organizational network (Bratkovic et al., 2009; Stam et al., 2014). Some scholars considered social networks We review the theories of social network and the growth of individual resources (Arroteia & Hafeez, 2020), while it also entrepreneurial enterprises in four parts: the growth of entre- referred to organizational resources. Few ventures could preneurial enterprises, network properties, network types, operate successfully without the relationship between orga- and gaps identified from the literature review. nizations and other organizations (Donnell et al., 2001). Whether personal or organizational network plays a more The Growth of Entrepreneurial Enterprises significant effect on the growth of entrepreneurial enterprises should be further studied. Also, social network of entrepre- Social network can provide valuable resources that entrepre- neurial enterprises and that of entrepreneurs are not identical, neurial enterprises need to acquire, including tangible while this problem has been neglected. Both organizational resources and knowledge, advice, and emotional support and personal networks impact social networks (Donnell (Arregle et al., 2015). It can affect an entrepreneurial enter- et al., 2001), and they may influence differently on the prise’s economic performance through many channels growth of entrepreneurial enterprises. The existing research (Casson & Giusta, 2007). An entrepreneurial enterprise focused on the influence of network types on new venture could not grow well without contacting other entrepreneurs internationalization (Manolova et al., 2010), on the process or organizations (Donnell et al., 2001). If an entrepreneurial of entrepreneurship (Turner & Pennington, 2015), and enterprise wants to build a new venture, entrepreneurs or reviewed different network types (Donnell et al., 2001). It entrepreneurial teams should contact the government to needs to be further researched about the impact of network apply for new ventures’ qualifications, do relevant proce- types between network properties and the growth, and it may dures, obtain entrepreneurial policies, etc. Social network explain why there existed different ideas about the influence can give birth to entrepreneurial enterprises, and their net- of network properties on the growth of entrepreneurial enter- work properties play an important role in the growth of prises. This paper devotes itself to answering the following entrepreneurial enterprises (Fernández-Pérez et al., 2016; H. questions. (1) How do network properties (network size, net- Yang & Dess, 2007). work density, and tie strength) influence the growth of gen- Entrepreneurial enterprises often face numerous restric- eral entrepreneurial enterprises? (2) Do network types tions on access to or control over resources. Even without a (organizational and personal network) have impacts on the clear concept of the source of competitive advantage, the network properties-growth relationship? speed and probability of failure may be faster than that of We try to research the positive influence of network prop- mature enterprises. Entrepreneurs have a challenging period erties on the growth of entrepreneurial enterprises. Network to find venture capital, get governmental approval, study cus- size, network density, and tie strength are three key properties tomers etc. which all were growing venture needs in their of social network (Heirati et al., 2013; Mbura, 2015; Rooks social network (Cui et al., 2018). Social network is a crucial et al., 2014). There were also different sounds about the rela- mechanism for entrepreneurial enterprises to collect resources, tionship between network properties and the growth of entre- information, and assets. Social network required for the preneurial enterprises. While network properties also refer to growth of an entrepreneurial enterprise includes all kinds of Peng et al. 3 resources embedded in and derived from a network owned by or company’s value, entrepreneurs’ personal network pro- an individual or a social institution. It promotes entrepreneur- motes the growth of entrepreneurial enterprises in the early ial action operating well (Ndofor & Priem, 2011). It helps stage of entrepreneurship. While in the middle stage, an enter- enhance enterprises’ opportunities to obtain potential custom- prise needs to develop its partnerships network (Gu & Su, ers’ demands, new sales markets, or market segmentation. 2018) or alliance network (Goerzen, 2007) to extend its busi- The ability to obtain resources has a decisive effect on the ness, which refers to organizational network. Relatively growth of entrepreneurial enterprises (Ge et al., 2009). While speaking, inter-organizational network connects different the sources of entrepreneurial resources are largely dependent organizational networks and spans different organizations. on the supply of social network, and the environmental impact There is not a clear boundary of inter-organizational network seems to be secondary (Volpe & Biferali, 2008). (Bergenholtz & Waldstrøm, 2011). Elements of social net- work are usually people, either individuals or social units, for instance, families and clubs (Casson & Giusta, 2007). Network Properties Compared with prior research, all network types could be cat- Social network has many properties, such as network size, egorized as personal and organizational networks. network density, tie strength, etc. When Arregle et al. (2015) Personal network is sometimes called individual network, studied family ties in entrepreneurs’ social networks and new such as entrepreneurs’ network (Klyver & Christensen, 2007), venture growth, they thought network size was one of the or personal contact network (Donnell et al., 2001). The avail- most important control variables. When it comes to family ability and value of personal network could explain why ties, scholars thought tie strength was divided into strong ties some people could build a new venture and others not. and weak ties, that family ties belonged to the former ties Personal network usually helps entrepreneurs look for buyers (Jenssen & Greve, 2002). Besides, network density was and suppliers, which could promote the growth of entrepre- another valuable network control (Bahlmann, 2014; Zhou neurial enterprises (Batjargal, 2005a), for example, enter- et al., 2020). Network properties also include network diver- prises’ revenue growth. While organizational network means sity, structural holes, and network cohesion, but network a firm’s network, an entrepreneurial team and so on (Demirkan size, network density, and tie strength were the three main et al., 2013; Omri & Boujelben, 2015), it refers to an entrepre- properties. For instance, network diversity was changed by neurial team or a sub-company or different department of a adding and dropping numbers of partners to increase the firm, the tie between them may occur in an internal network. diversity of information (Demirkan et al., 2013), and it was Sub-organization is one part of organizational network, and it based on the existence of network size. The distant or non- contains joint ventures, franchise chains, strategic alliances, existent relationship between two network members is called and so on (Turner & Pennington, 2015). These styles of the structural holes closely associated with network density and new organizational network bring more advantages to tie strength (Batjargal, 2005b; Tang et al., 2020). increase original entrepreneurial enterprises. It is usually Hansen (1995) studied entrepreneurial network earlier, described as a special system that connects units, divisions, employing network size, network density, and tie strength to and networks. It plays a vital role in the growth of entrepre- describe the entrepreneurial action set variables. It was the neurial enterprises and personal networks. same with Mbura (2015) ideas that this kind of network anal- ysis could consider both social network structure and con- Hypotheses Development tent. Rooks et al. (2014) believed that social network should fall into network level and relational level, which meant the Referring to our study, we propose six hypotheses: the effects structure and content of the network. From the content of of network properties on the growth of entrepreneurial enter- their studies, that was to say, social network could be com- prises, and the moderators of personal network, organiza- posed by network size, network density, and tie strength. tional network between these two variables. Therefore, we take network size, network density, and tie As for correlation, we followed three steps: In the first step, strength as our main network properties. we put forward our idea and then explain why the positive side exists. In the second step, we explain why its opposition from its opposite side is not good. In the third step, we offer opin- Network Types ions on how the positive side influences and what benefits can According to the characteristics of a network, entrepreneurs create for the growth of entrepreneurial enterprises. may need a competitive or supportive network (Das & As for the moderator, the first and third steps are similar Goswami, 2019; Prajapati & Biswas, 2011) that refers to per- to the steps for correlation mentioned above. In the second sonal network. If we want to achieve the growth of entrepre- step, we put forward the reason for both organization net- neurial enterprises, we should focus on the enterprises’ formal work and personal network having a moderating effect on organizational structures and more individuals’ and groups’ the growth of entrepreneurial enterprises and explain why informal relationships (Hemphälä & Magnusson, 2012). the moderating effect of organization network and personal Under the status of small resources without the effect of brand network was greater. 4 SAGE Open size is limited to family and friends, relatives, government, Network Size and the Growth of Entrepreneurial and financial institutions (Das & Goswami, 2019; Prajapati Enterprises & Biswas, 2011). While organizational network that concluded Expansion of network size of social network can increase the with alliance networks could provide more firm’s competi- extent to which entrepreneurial enterprises gain access to tive activities (Chi et al., 2010), making the enterprise build resources through the network (J. Yang et al., 2011). The size its competitive network to grow fast. Thus, we proposed: of network becoming large means more contacts, and the combined amount of information every member carries will Hypothesis 2: Network size is more positively related to be multiple quantities. More network members might explore the growth of entrepreneurial enterprises in organisational more new knowledge and increase the knowledge they network than personal network. receive (Fernández-Pérez et al., 2016). Research has shown that a large network provides a greater possibility to collect Network Density and the Growth of information than a small one (Fernández-Pérez et al., 2016). Entrepreneurial Enterprises Expanding the size of social network can promote access to more quantity and quality of entrepreneurial resources, Network density measured whether the link of entrepreneur- thereby improving the efficiency of access to entrepreneurial ial enterprises is dense or sparse. When the possible contacts resources and thus achieving sustainable competitive advan- are fixed, density depends on the number of current ties. The tages (Ge et al., 2009). While with little contact with others, network density becomes great, and the number of members the quantity of information and resource brought by a net- at a certain time could contact other people is huge (H. Yang work member is limited as well as the total quantity. From & Dess, 2007). Numerous contacts may offer the necessary the upstream perspective of stakeholders, little information resources that enterprises need. An intensive network gener- about suppliers may increase the operation cost of the start- ates redundant information (Granovetter, 1973), and over- ups. From the downstream perspective of stakeholders, sel- lapping information is useless to foresee trends in products dom information about customers may lead to a tiny market and markets for entrepreneurial enterprises (H. Yang & Dess, share. All of these would result in low impeding the growth 2007). Rather than helping entrepreneurial enterprises of entrepreneurial enterprises. In fact, entrepreneurial enter- grow, it consumes resources and hinders enterprises’ growth, prises whose broad networks are more successful and may bringing fewer consumers. Sparse network provides access have a greater possibility of growth (Lamine et al., 2017). A to new, valuable information (Jenssen & Greve, 2002). large network brings more chances for entrepreneurs to Although few ties exist, people or organizations could not increase their creativity and improve their ability to imple- create a close or monopolistic network, and entrepreneurial ment innovative ideas (Fernández-Pérez et al., 2016). Thus, enterprises could seek resources without market threat. we proposed: Diverse resources from sparse network make entrepreneurial Hypothesis 1: Network size has a significant positive enterprises more likely to enter the dominant market (Ndofor effect on the growth of entrepreneurial enterprises. Personal & Priem, 2011). However, dense network tends to give rise network refers to the network of entrepreneurs, CEOs, and to exclusive rights among leaders, and it is easy to lead to managers, while organizational network refers to networks arbitrary decision-making. Although dense network helps of entrepreneurial teams and sub-organizations or coopera- form a normative network and enhances trust and coopera- tion partners, such as joint ventures and franchise chains tion among network members, the consistency of dense net- (Turner & Pennington, 2015). Both personal and organiza- work often hinders enterprise creativity that is harmful to the tional networks provide the possibility of members’ contact, development of enterprises (H. Yang & Dess, 2007), reduces while their effectiveness may go through different ways in the probability of effective information appearing, and an entrepreneurial enterprise. From the perspective of quan- restrains the growth of entrepreneurial enterprises (H. Yang tity, organizational network may produce much more con- & Dess, 2007). Thus, we proposed: tacts than personal network. A firm with a larger size of the alliance network could help itself get access to more Hypothesis 3: Network density has a significant negative resources (Milanov & Fernhaber, 2009), including resources impact on the growth of entrepreneurial enterprises. from sectors, suppliers, or alliances. Organizational network Based on the above hypothesis, personal network’s density can help the firm to connect with buyers (R. P. Lee et al., impacts more positively on the growth of entrepreneurial 2011), suppliers (Bergenholtz & Waldstrøm, 2011), and part- enterprises than organizational network’s density does. From ners (Goerzen, 2007; Karamanos, 2012). Although personal the perspective of stakeholders theory, personal network refers network can also get in touch with some buyers, it gives buy- to entrepreneurs’ close ties such as friends and family (Jenssen ers smaller trust than organizational network. The status and & Greve, 2002), and their current ties provide a dense net- reputation of organizational network may bring more coop- work. Such a tight network tends to weaken employees’ eration and market share. To some extent, personal network’s Peng et al. 5 enthusiasm for work, which is not conducive to the growth of Then, it can help member enterprises improve the results of entrepreneurial enterprises. While organizational network risk identification, reduce the probability of failure and pro- refers to an enterprise’s external network that could bring the mote an increase in entrepreneurial income (J. Yang & chance of cooperation with customers, suppliers, government, Zhang, 2015). and competitors. Too tight ties between organization networks are likely to bring unfair competition or increase the depen- Hypothesis 5: Tie strength has a significant positive dence of the entrepreneurial enterprise on the other organiza- impact on the growth of entrepreneurial enterprises. tions, but on the contrary, weaken their competitive advantages and bargaining power. Personal network in dense network Based on the above hypothesis, personal network’s tie bringing overlap and obsolete information tends to be a barrier strength impacts more positively on the growth of entrepre- to entry of new information (Prajapati & Biswas, 2011), while neurial enterprises than organizational network does. organizational network being dense may enhance the degree Personal network’s closest relationship among members of barrier existing, for a reason that dense network causes the could operate their network to tap into the advice network enterprise’s operations transparent which may lead itself to be (Manolova et al., 2010). Advice network often occurs in passive for product pricing or profit capture. Sparse personal mutual trust among network members, through intimate, network could bring more different information for enter- long-time, and frequent communication. That is to say, tie prise’s innovation and development, as well as sparse organi- strength could help offer more believable advice. In a limited zational network. There exist many personality differences amount of time, organizational network may tend to be weak among network links in organizational network (Turner & ties, and it may take much more time to keep up with organi- Pennington, 2015). Differences are bigger than personal net- zational network’s members than personal’s (Hansen, 1995). works’. Dense network is easier to overlap information (Singh Personal network tends to be direct ties with network mem- et al., 2000), organizational network can mitigate this overlap. bers, and they may have known each other before. It increases Through organizational network, entrepreneurs could catch the trust of network links, can enhance interaction with net- opportunities easily in sparse network (Batjargal, 2005b). work members, and is easy for entrepreneurs to build emo- Thus, we proposed: tions with them in a short time (Bratkovic et al., 2009). However, organizational network always represents its Hypothesis 4: Network density is more negatively related enterprise to contact buyers, suppliers, government, banks, to the growth of entrepreneurial enterprises in organisa- or others, before it gets the brand’s effectiveness. It might be tional network than personal network. hard to get trust with them getting commercial transactions from a new organization. While personal network has been most frequently employed in a newly created firm, personal Tie Strength and the Growth of Entrepreneurial network based on entrepreneurs’ egocentric network that Enterprises provides advice could serve as an informal safeguard against potential opportunistic behaviours from mutual acquaintances Many scholars believe that tie strength is necessary for the (Mahmood et al., 2011), compared with organizational net- acquisition and growth of early resources in the primary work, it could save more time, money, resources, or other period of establishing an enterprise. Strong ties make enter- energies in information search. Thus, we proposed: prises expand the market or purchase fixed assets (Ge et al., 2009). They come from the closest circle of friends and fam- Hypothesis 6: Tie strength is more positively related to ily members (Cantner & Stützer, 2010), bring higher emo- the growth of entrepreneurial enterprises in personal net- tional intensity and closer ties (Zhang & Cao, 2007), and work than organisational network. promote the identification, development, and utilization of information (J. Yang & Zhang, 2015). Repeated collabora- tion gives entrepreneurs closer trust (J. Yang & Zhang, 2015) Conceptual Model and enhances potential cooperation (Demirkan et al., 2013), which reduces the cost of information assessment and vali- As mentioned above, we could propose a conceptual model, dation. While weak ties weaken connections between mem- as shown in Figure 1. (we employ Visio software to create bers, there is no trust among companions. How to complete the artwork throughout our study). Both network size and tie production transaction and profit distribution have become a strength are positively related to the growth of entrepreneur- controversial problem. Conflicts between interest subjects ial enterprises. Network density is significantly negative for will affect the growth of entrepreneurial enterprises. Closer growth. The relationship between network size and growth is trust has many additional functions. First, it can enhance stronger for organizational network and network density. information exchange and integration; promote close com- While the relationship between tie strength and growth is munication and mutual learning among network members. stronger for personal network. 6 SAGE Open Figure 1. Conceptual model. Rauch et al. (2016) for the study. We used combinations of Methods keywords related to network size (e.g., the size of network, This study employs meta-analysis to research the relationship network size, network range, and network scale), network between social network and the growth of entrepreneurial density (e.g., the density of network and network density), enterprises. We used the meta-analytic approach for two rea- tie strength (e.g., network strength and tie strength), and the sons. Firstly, there are different sounds about the relationship growth of entrepreneurial enterprises (e.g., firm growth, of social network to the growth of entrepreneurial enterprises sale growth, and profit growth). By reading through down- based on the sight of network type. While meta-analysis is a loaded references, we got the definitions and measurement tool of merger statistics, it can be used to aggregate and pro- indicators of previously selected keywords, expanded the cess independent research results with the same research range of keywords combined, and searched databases again objective (Bierwerth et al., 2015; Schwens et al., 2018; Stam until there were no new related references. The search et al., 2014; Zhao et al., 2021). The meta-analytic approach terms help us to collect a number of references and to can evaluate the total correlation between variables and offer collect a number of references and understand the relation- us the size of variables’ relationship. Secondly, the meta-ana- ship between social network attributes and the growth of lytic approach has been widely applied in the field of entre- entrepreneurial enterprises. preneurship research by many scholars. It is a new Then we set five steps to get related empirical articles that comprehensive literature analysis method combining qualita- we need. Firstly, we searched official databases: Elsevier tive and quantitative analysis (Bierwerth et al., 2015; Schwens Science Direct, Web of Science, Google Scholar, EBSCOhost, et al., 2018; Stam et al., 2014; Zhao et al., 2021). Through the JSTOR, and Psyclnfo by combining keywords (Mrabet & secondary analysis of the existing research data, combined Ellouze, 2014). Secondly, we manually went through the with the existing development environment and situation, principal entrepreneurship, management, and business jour- effective suggestions and solutions suitable for modern devel- nals, such as Small Business Economics, Entrepreneurship opment can be obtained. In addition, the number of hypothe- Theory and Practice, Academy of Management Journal, and ses does not influence the application of the meta-analytic Academy of Management Review. This step aims to supple- approach. There were more than six hypotheses in the previ- ment the scope of reference retrieval and make the retrieval ous study by Stam et al. (2014) and Rauch et al. (2016). Their more comprehensive. Because some studies may be unpub- studies also focused on firm performance. As for our study, lished in UTD and FT, but they were already online. And we we set two steps. At first, we define search strategy and inclu- were searching the selected journals for other cited articles sion criteria, including network size, network density, tie that may be helpful. Thirdly, we searched databases of SSRN, strength, and the growth of entrepreneurial enterprises. Then, conference proceedings of the Academy of Management and we describe meta-analytic procedures and illustrate selected Babson College Entrepreneurship Research Conference, data that we need to calculate. searching for unpublished literature to reduce publication bias. Fourthly, we used the correlation coefficient to respond to effect sizes of network properties, network types, and the Search Strategy and Inclusion Criteria growth of entrepreneurial enterprises. This paper tries to use First of all, we need to define search strategy and inclusion the harmonic average, and the algorithm has been exten- criteria. We followed the idea of Stam et al. (2014) and sively used in the field of entrepreneurship (Rosenbusch Peng et al. 7 Table 1. Literature Screening Results. Organizational Personal Pieces of Total Relationship between variables network (ON) network (PN) reference samples Network size to the growth of entrepreneurial enterprises (SG) 8 10 18 2,975 Network density to the growth of entrepreneurial enterprises (DG) 3 3 6 1,158 Tie strength to the growth of entrepreneurial enterprises (TG) 11 18 29 5,119 Records identified through database Additional records identified retrieving (n=821) through other sources (n=65) Duplicated articles removed Articles excluded based on initial (n=833) screen (n=383) Excluded due irrelevant to Title and abstracts screeded (n=450) entrepreneurship (n=233) Excluded due effect sizes Full-text articles assessed for inconsistent with requirement eligibility (n=217) (n=189) Studies included in quantitiative synthesis(meta-analysis) (n=28) Figure 2. Flow chart of the references search process. et al., 2013; Schwens et al., 2018). Fifthly, if two or more Clark (2003), network range meant the different connections references were used for the same samples, we chose the ear- or network diversity. lier one. If a reference reported multiple independent sam- Network size. It reflects the number of relationships indi- ples, we code them several times. Finally, we got 28 viduals maintain in the social network or organization they quantitative empirical articles containing 31 independent did business with (Prajapati & Biswas, 2011; Premaratne, samples with 5,259 observations shown in Table 1, and the 2002). We can measure it by calculating the total number of retrieval process was illustrated in Figure 2. possible contacts. We used the following keywords: network We mainly searched keywords according to the following size (Batjargal et al., 2013; Scholten, 2006), network range criteria. At first, we searched the selected combined key- (Ge et al., 2009), network scale (J. Yang et al., 2011), breadth words such as network size and the growth of entrepreneurial of external communication and number of partners (D. Y. enterprise. We ensure the definition and measurement by Lee & Tsang, 2001), etc. It should note that network range reading the selected journals. And then, we explicitly include represented the different connections or network diversity and exclude keywords by reading their definition and mea- (Collins & Clark, 2003), while network size indicated the surement carefully. For example, when we searched data on number of connections(Batjargal et al., 2013). network size to the growth of entrepreneurial enterprises, we used network range to search for related network size refer- Network density. It is a proportion of identified contacts ences. In reference Ge et al. (2009), network range meant the present out of the total possible contacts (Premaratne, number of network members, while in reference Collins and 2002). We can measure it by calculating the total number 8 SAGE Open of identified contacts divided by the total possible numbers growth, market share growth, employ/employment growth, of network members, while the total number of possible ties organization growth, and stock growth. Secondly, taking equals network size. So network density ranges from 0.0 to the growth rate to measure venture/firm growth, such as 1.0. It tended to measure the collective social capital avail- sales and profit growth rates. Thirdly, employing growth able to all members of the network, which could be divided speed, sales growth speed, new employees increase speed, into sparse and close networks (Ge et al., 2009). Meanwhile, market share growth speed, and net earnings growth speed. it was measured by the degree to which social networks are Fourthly, when referring to the growth, scholars collected closely connected (Hoang & Antoncic, 2003). When the data by collecting a new venture’s first year’s performance, network density was relatively high, all network members such as first year and first 5 years. Fifthly, entrepreneurship communicated and interacted with each other (Liu et al., performance was measured in the venture-growth stage. 2009). The main keywords found in the retrieving process To improve coding reliability, the first and second authors were as follows: density (Bhagavatula et al., 2010; Prajapati both coded the studies. Characteristics of 28 quantitative & Biswas, 2011; Scholten, 2006), network density (Batjargal empirical articles are shown in Table 2. et al., 2013; Scholten, 2006), degree (Hansen, 1995). Meta-Analytic Procedures Tie strength. It is measured by the duration of the relation- ship, the intimacy of the relationship, the frequency of com- First, we test whether we could research by meta-analysis. munication, etc. (Ge et al., 2009; Jenssen & Greve, 2002). We follow the research role of meta-analysis. No less than 20 Tie strength was related to the communication time and the documents are recommended for inclusion in the analysis. degree of emotional intimacy and mutual trust of the mem- No less than three papers for single group inclusion analysis bers of the network (J. Yang et al., 2011). Tie strength usually of combinatorial meta-analysis are used as criteria. We test comes from the closest circle of friends and family members the statistical heterogeneity of the study with Q statistics. (Cantner & Stützer, 2010), which refers to the direct ties, After that, we quantise it with I-squared (I ) to test the effects including trust, reciprocity, embedding, etc. (Granovetter, of heterogeneity among studies. If p-values (p1) < .05, 2 2 1973; Scholten, 2006). We used keywords as follows: net- I > 50%, indicating that there is heterogeneity (I > 75%, work strength (J. Yang et al., 2011), network intensity (Brat- the extent of heterogeneity is high), the random effect model kovic et al., 2009; Ge et al., 2009), tie strength (Musteen is selected. On the contrary, the fixed-effect model is selected et al., 2013; Scholten, 2006) etc. We excluded descriptions (Stam et al., 2014). However, if p-values (p1) < .05, I < 50%, about weak ties among tie strength. indicating a low heterogeneity among studies. That is to say, the research result of these variables is consistent. Organizational and personal network. As for personal net- Since publication bias may be a serious problem in the work, we chose keywords including CEOs’ external social meta-analysis (Schwens et al., 2018), we use Duval and network (Fernández-Pérez et al., 2016; Musteen et al., 2010), Tweedie’s trim and fill tests, Begg and Mazumdar test, and employees’ network (Hemphälä & Magnusson, 2012), firm Egger test to test the potential publication bias, in which Duval owners’ network (Manev et al., 2005), and entrepreneur’s and Tweedie’s trim and fill tests need to be adjusted to achieve network (Klyver & Christensen, 2007). As for organiza- symmetry in the funnel plot. The funnel graph is not symmet- tional network, we chose keywords including firms’ initial ric, indicating that the difference between observed and networks (Demirkan et al., 2013), entrepreneurial team’s adjusted values is more than 0.1 (i.e., Δr > .1). The Egger test network (Omri & Boujelben, 2015), a network in collectiv- uses the slope of the regression line to represent the normaliza- istic context (Rooks et al., 2014), external partnerships (Gu tion effect, and the regression intercept value is significant & Su, 2018). Following with ideas of Turner and Pennington (i.e., p2 > .1). Begg Mazumdar test uses the level correlation (2015), organizational network also contained alliance net- between the effect size and the standard error, and the rank works (Rowley et al., 2000), and cluster ties (Li et al., 2013). correlation is significant (i.e., p3 < .1). Only when all results of the three tests meet the above values, indicate the existence The growth of entrepreneurial enterprises. The success of publication bias that this study is considered to have a seri- of entrepreneurial enterprises can be measured by survival ous impact on publication bias (Schwens et al., 2018). and growth (Semrau & Werner, 2014), while survival tends to be a minimum criterion of success. Growth is a vital Results entrepreneurship performance outcome because it confers entrepreneurial enterprises with increased abilities, powers, First, the heterogeneity test results showed that the p-value and profits (Vissa & Chacar, 2005). Prior studies referred of the relationship between three network properties and the to five ways to measure it. They are, firstly, conceptual- growth of entrepreneurial enterprises was less than .01. izing related indicator growth, such as sales growth, profit Results of all organizational network properties to the growth Peng et al. 9 Table 2. Independent Samples. Publication Type of social Number Authors (year) N Countries status SG DG TG network Construct labels 1 Arregle et al. 515 China, Russia, Pub .107 .073 PN Network size, family ties, and (2015) France, and revenue growth America 2 Batjargal (2000) 75 Russia Unpub .110 .000 PN Network size, strong ties, and sales growth 3 Batjargal 159 China and Unpub −.050 .085 −.215 PN Network size, network density, (2005a) Russia tie strength, and revenue growth 4 Batjargal 56 Russia Pub .090 PN Network size and revenue (2005b) growth 5 Batjargal et al. 637 China, Russia, Pub .060 −.170 −.020 PN Network size, network (2013) France, and density, family ties, and America revenue growth 6 Bradley et al. 201 Dominica Pub −.090 PN Strong ties and profit growth (2012) and Kenya 7 Bratkovic et al. 103 Slovenia Pub .107 PN Resource network (2009) intensity + central network person contact + central network person friendship and sales growth 8 Cantner and 182 Germany Pub −.090 PN Strong ties and employee Stützer (2010) growth 274 Germany .030 ON 9 Castro et al. 126 Colombia Pub .064 .102 ON Network size, strong ties, (2014) andrevenue growth 10 Collins and 73 America Pub .190 .155 ON External network + internal Clark (2003) network size, external network strength of ties, and sales growth + stock growth 11 Danis et al. 117 Hungary Pub .260 ON Networking intensity and (2010) sales growth + revenue 182 Hungary Pub .010 ON growth + employee growth 12 Ge et al. (2009) 177 China Pub .071 .183 ON Network range, network intensity, and revenue growth + sales growth + employee growth 13 Hansen (1995) 44 America Pub .530 .480 −.080 ON Network size, network density, frequency, and organization growth 14 Gu and Su 177 China Pub .071 .183 ON Network range, network (2018) intensity, and sales growth + employment growth + market share growth 15 Jones and 211 England Pub .220 PN Strong ties and sales Jayawarna growth + turnover growth (2010) 16 D. Y. Lee and 168 Singapore Pub .191 .280 PN Number of partners + breadth Tsang (2001) of external communication, frequency of external communication, and venture growth 17 Manev et al. 160 Bulgaria Pub .100 PN Strong ties and employee (2005) growth 18 Musteen et al. 169 Czech Pub .140 .180 PN International network density, (2013) international network tie strength, and sales growth (continued) 10 SAGE Open Table 2. (continued) Publication Type of social Number Authors (year) N Countries status SG DG TG network Construct labels 19 Ostgaard and 159 England Pub −.024 −.080 PN Size of networks, the Birley (1996) intensity of relationship of personal networks, and sales growth + profit growth + employment growth 20 Sawyerr et al. 153 America Pub .127 .177 PN Frequency and number of (2003) contacts and sales growth 21 Scholten (2006) 65 Holland Unpub .170 −.050 −.090 ON Network size, tie strength, network density, and employee growth 22 Semrau and 146 Germany Pub .095 .065 PN Network size, tie strength, Sigmund and revenue growth + profit (2012) growth + employment growth 23 Vissa and 84 India Pub .250 −.340 ON Network size, network Chacar (2005) density, and revenue growth 24 J. Yang et al. 130 China Unpub .629 .606 PN Network scale, network (2011) strength, and net earnings growth + sales growth + employees growth + market share growth 25 Zhang and Cao 91 China Pub .248 ON Tie strength and sale (2007) growth + profit growth + market share growth + employees growth 26 X. Zhao et al. 133 China Pub .233 −.060 PN Business network (2010) size + government network size and employee growth + business growth 75 China .318 .310 PN Business network size + government network size and asset growth + business growth 27 L. Zhao and 210 China Pub .364 PN Strong ties and fast growth Ha-Brookshire (2018) 28 Zou et al. 252 China Pub .000 PN Strong ties and organic (2010) growth + partnership growth + acquisition growth Note. Pub = published; Unpub = unpublished; PN = personal network; ON = organizational network. in I were less than 50%. Most scholars’ current views on by Stam et al. (2014). The paper analyzed the significance organizational network were consistent. I of personal net- of the relationship between social network and the growth of work and overall network were almost closest to 75%, so entrepreneurial enterprises. Also, social network would be there exists high heterogeneous between these variables. more positively related to the growth of entrepreneurial From Table 3, all results indicated that there was no obvi- enterprises in personal network than organizational network ous publication bias. (r = .097 < r = .129, p = .000 < .001, p = .002 < .01). og pg og pg Next, we assessed the impact of network size, network Network size and tie strength had a positively significant density, and tie strength on the growth of entrepreneurial impact on the growth of entrepreneurial enterprises enterprises. The overall relationship between the social net- (r = .164 > 0, p < .001; r = .100 > 0, p = .002 < .01), sg sg tg tg work and the growth of entrepreneurial enterprises was pos- while network density had no significant negative effect on itively significant (r = .115, p < .001), it was recognized the growth of entrepreneurial enterprises (p = .901 > .1). ng ng dg Peng et al. 11 Table 3. The results of comparative analysis. Trim and fill Egger B&M Variable k N r 95% CI p1 I ik Δr p2 p3 NG (network-growth) 31 5,259 .115 [0.057,0.172] .000 76.467 9 .081 .070 .122 ON-growth (OG) 14 1,573 .097 [0.050,0.143] .000 49.020 3 .030 .066 .171 PN-growth (PG 19 3,712 .129 [0.047,0.210] .002 83.423 0 .000 .127 .363 SG-growth (SG) 18 2,975 .164 [0.086,0.240] .000 75.845 6 .086 .114 .049 ON-SG-growth (OSG) 8 777 .174 [0.104,0.243] .000 0.075 3 .041 .062 .386 PN-SG-growth (PSG) 10 2,198 .146 [0.029,0.259] .014 85.300 0 .000 .400 .531 DG-growth (DG) 6 1,158 .012 [-0.176,0.199] .901 87.070 1 .085 .275 .452 ON-DG-growth (ODG) 3 193 .029 [-0.420,0.467] .904 90.451 2 .369 .005 .296 PN-DG-growth (PDG) 3 965 .010 [-0.205,0.224] .928 88.680 2 .180 .100 .602 TG-growth (TG) 29 5,119 .100 [0.037,0.162] .002 79.731 5 .061 .286 .311 ON-TG-growth (OTG) 11 1,281 .077 [0.005,0.149] .037 45.917 0 .000 .737 .697 PN-TG-growth (PTG) 18 3,656 .132 [0.041,0.220] .004 86.324 4 .081 .250 .596 Note. k = the number of samples; N = the number of observations; r = weighted mean observed correlations; 95% CI = 95% confidence interval; p1 = the p-value of test about variables; I = the I-squared of heterogeneity test; ik = the number of studies trimmed; Δr = difference between observed values and adjusted values; p2 = the p-value of Egger’s regression intercept test; p3 = the p-value of Begg and Mazumdar rank correlation test. Hypothesis 1 and Hypothesis 5 were accepted, while Table 4. The Results of Hypotheses. Hypothesis 3 and Hypothesis 4 were rejected. Hypotheses Results Hypotheses Results Finally, network size was more significantly positive related to the growth of entrepreneurial enterprises in organi- H1 Supported H4 Not supported zational network than personal network (r = .174 > r = .146, H2 Supported H5 Supported osg psg p < .001, p = .014 < .05), tie strength was more signifi- H3 Not supported H6 Supported osg psg cantly and positively related to the growth of entrepreneurial enterprises in personal network than organizational network strangers to join them. Keeping a large network leads to an (r = .077 < r = .132, p = .037 < .01, p = .004 < .01). otg ptg otg ptg increased potential for goal and value conflicts among addi- Hypothesis 2 and Hypothesis 6 were supported. tional network members, and it is challenging to manage effectively (Demirkan et al., 2013). Therefore, there might Discussion be a threshold of network size for the growth of entrepre- In the end, we obtained these results shown in Table 4. neurial enterprises. When it exceeds this threshold, network From Hypothesis 1, we find that the impact of network size would weaken the effect on the growth and even hinder size on the growth of entrepreneurial enterprises is signifi- entrepreneurial enterprises’ growth. Network size extending cant positively. This is in line with the many views of the under this threshold can promote growth significantly. academic community. Fernández-Pérez et al. (2016), Diánez- Besides, the expansion of network size is the increase in the González and Camelo-Ordaz (2019), Sullivan and Marvel network members and the quality. (2011), and others believed that network size determined the From Hypothesis 2, we find that organizational network scope of activities of entrepreneurs or entrepreneurial enter- enhances the influence of network size on the growth of prises, and it was consistent with the research results of entrepreneurial enterprises is larger significant positively Milanov and Fernhaber (2009), R. P. Lee et al. (2011), and than personal network. A larger network contained more Bergenholtz and Waldstrøm (2011). A larger network opens information about the top management team’s organizations the possibility of more information and resources for entre- (Collins & Clark, 2003). Three years after start-up, entrepre- preneurial enterprises. However, it contradicted the results of neurs should expand their network size into developing busi- Hansen (1995) because every time a network member was nesses (Ostgaard & Birley, 1996). Organizational networks added to the social network, the overall benefit of the enter- include many types of relationships, such as strategic part- prise would be reduced. When an entrepreneur builds a firm, ners, suppliers, and customers. A larger network size made a larger network will not promote growth in the first 3 years other customers believe that the current firm might create (Batjargal, 2005a). A network with a low rate of strangers more possibilities for benefits (R. P. Lee et al., 2011). tended to enhance the growth (Ostgaard & Birley, 1996), and Besides, organizational network likes to build alliances to entrepreneurs expanding their network may attract more increase the enterprises’ performance (Raz & Gloor, 2007). 12 SAGE Open While some scholars might hold different ideas (D. Y. Lee & of strengthening their networks (X. Zhao et al., 2010), it Tsang, 2001; Musteen et al., 2010). An entrepreneurial enter- constrained enterprises’ development (Castro et al., 2014). prise with many founders may have higher opportunities of Maintaining tie strength costs much time and money it succeeding (D. Y. Lee & Tsang, 2001), and cooperation with reduces current assets and strains the capacity of growing other partners is only for entrepreneurs’ charisma. But per- businesses. We believed that tie strength also has a thresh- sonal network may produce contradictions among arbitrary old to enhance the growth of entrepreneurial enterprises. decisions, for example, it may occur complacency, and some From Hypothesis 6, personal network increasing the util- information spots could hinder the development of entrepre- ity of tie strength in the growth of entrepreneurial enterprises neurial enterprises (Musteen et al., 2010). is larger and significantly positive than organizational net- From Hypothesis 3 and Hypothesis 4, it indicated that net- work. It was the same with the view of many scholars. Many work density does not correlate with the growth of entrepre- scholars researched personal network’s properties, and either neurial enterprises. This conflicts with the ideas of Batjargal in a personal network or an organizational network, tie et al. (2013), Scholten (2006), etc. Comparing with these strength had a significant positive correlation to the growth. studies, differences may come from structural holes embed- Strong ties helped to obtain much trust among members con- ded into social network. Musteen et al. (2013) took structural taining suppliers and customers (J. Yang & Zhang, 2015). holes into the attribute of network density and thought that Personal network was often closely linked to acquaintances, network density reflected structural holes to a certain extent: families, and friends which were usually considered a strong High density, few structural holes. Different structural holes tie (Rooks et al., 2014). Ties in an open network were related may be in the same density network. There was a stronger to different organizations from each other (Assudani, 2009). possibility in a sparse network with many structural holes that An open network was usually along with weak ties (Mahmood provided more heterogeneous information (Scholten, 2006). et al., 2011) that led the entrepreneurial enterprise to grow As for scholars Batjargal (2005b) and Das and Goswami slowly. Based on personal network, advice sharing relied on (2019), network centrality, network heterogeneity, or struc- trust among entrepreneurs’ closely individual network, tural holes were embedded into social network, and they posi- which would decrease the cost of information acquisition tively affected the function of network density to promote the (Manolova et al., 2010). Information travelled faster through growth of entrepreneurial enterprises. It would be some influ- personal network, and it was easier for a person to identify ences between network density and centrality, heterogeneity, the valuable and potential suppliers or customers or linkers and structural holes. They all contribute to diverse informa- than an organization to do, and then take time and energy to tion and resources. From scholar Batjargal (2005b) and his catch this relationship to apply for creating values. team’s two studies, they concluded two different results. The literature in 2005 held that network density positively corre- Practical Implications lated the growth, while the literature in 2013 held the opposite. Compared with the different results, maybe family ties and From a practical point of view, our research has two consid- internal ties easily tend to tie strength that influences the func- erable implications for managers. These measures are as tion of network density to the growth. We forecast that tie follows: strength may affect the relation between network density and First, the network size has a positive and significant cor- the growth of entrepreneurial enterprises. relation with the growth of entrepreneurial enterprises, and From Hypothesis 5, tie strength encourages the growth organizational network plays a positive moderator between of entrepreneurial enterprises significantly. Extensive inter- social network and the growth of entrepreneurial enterprises. action and high trust were conducive to obtaining suffi- There exists a threshold of network size when considering its cient, accurate, timely, and useful information (J. Yang & effect on the growth of entrepreneurial enterprises. In the Zhang, 2015), beneficial to developing enterprises’ prod- early stage of entrepreneurship, entrepreneurs should take ucts (Scholten, 2006). However, some scholars held the measures to expand their network size. Managers can allow opposite view (Bradley et al., 2012; Mahmood et al., 2011; employers to participate in other activities to know more peo- Ostgaard & Birley, 1996; Raz & Gloor, 2007; X. Zhao ple who may become potential buyers, suppliers, or partners. et al., 2010). Bradley et al. (2012) believed that the infor- Then, managers should divide all network relationships into mation exchanged with friends and relatives overlapped different groups, such as new or old relationships. Besides, with the information obtained in other ways, and overlap- managers should hold annual meetings, thank customer meet- ping information raised the cost of its acquirement. ings, and competitive promotions. They should participate Traditional methods by family and friends also reduced the in investment conferences to obtain innovative ideas and get sensitivity of entrepreneurial enterprises to innovation dis- in touch with different partners. Afterwards, they could set up covery (Bradley et al., 2012). Entrepreneurs preferred to an access system to allow external organizations to register take much time and money to contact others to obtain val- for regular business exchanges. Finally, they should partici- ues, while this connecting cost would counteract the values pate in various activities organized by different external Peng et al. 13 organizations and then identify potential buyers or suppliers properties to the growth of entrepreneurial enterprises, yet to establish regular visiting relationships. the other network (centrality, network heterogeneity, and Second, tie strength has a significant positive impact on structural holes.) are still not researched. Secondly, how net- the growth of entrepreneurial enterprises. Tie strength will be work properties influence each other also deserves research. more positively significant to the growth of entrepreneurial Given the limitation of our study, the future research enterprise in personal network than organizational network. scope includes: to conduct a similar study to explore the rela- There exists a threshold of tie strength when being given tionship among centrality, network heterogeneity, and struc- influence on the growth of entrepreneurial enterprises. In the tural holes, to explore the characteristics and mutual influence first stage, entrepreneurs should adopt measures to enhance between the properties, especially tie strength and network tie strength, and in the second stage, entrepreneurs should density. take ideas to get sparse networks to get much diverse infor- mation and resources. Managers should take certain mea- Declaration of Conflicting Interests sures to make network size large when in the early of The author(s) declared no potential conflicts of interest with respect entrepreneurship and utilize personal network’s function to to the research, authorship, and/or publication of this article. strengthen its tie strength to enhance entrepreneurial enter- prises’ growth. When in the growth of entrepreneurship, Funding managers should keep the current tie strength and dig the The author(s) disclosed receipt of the following financial support potential value of weak ties. At first, managers should permit for the research, authorship, and/or publication of this article: This network members to contact members’ individual networks research was funded by the National Social Science Project and keep all network members informed of the progress of Foundation (20FGLB007). projects or other activities in each department. They should also offer extra fees for network members to regularly visit ORCID iD existing and potential contacts, such as their indirect and Yang Liu https://orcid.org/0000-0001-8006-3236 direct friends. Next, managers should work closely with employees. Every employee is required to turn in a weekly report to the head of the department, letting the head know References their behaviour every day. Afterwards, managers should reg- Arregle, J. L., Batjargal, B., Hitt, M. A., Webb, J. W., Miller, T., ularly hold monthly meetings where the department head can & Tsui, A. S. (2015). Family ties in entrepreneurs’ social net- report monthly work and share information or resources to works and new venture growth. Entrepreneurship: Theory and deepen their relationship through activities. Besides, manag- Practice, 39(2), 313–344. https://doi.org/10.1111/etap.12044 ers should know the cost of developing tie strengths and Arroteia, N., & Hafeez, K. (2020). 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Publisher: SAGE
Copyright: © The Author(s) 2022
ISSN: 2158-2440
eISSN: 2158-2440
DOI: 10.1177/21582440221108178
Publisher site: See Article on Publisher Site

Abstract

Network size, network density, and tie strength together determine the function of social network and affect the growth of entrepreneurial enterprises. However, how the role of network size, network density, and tie strength on the growth of entrepreneurial enterprises remains inconsistent, as well as the effect of organizational and personal network remains unclear. To solve these relationships, we employ meta-analysis to reach study goals by researching 31 independent samples from 28 references with 5,259 observations. Results have shown two main findings: (1) Both network size and tie strength have a positive and significant impact on the growth of entrepreneurial enterprises, while network density does not correlate with the growth. (2) Organizational network mainly plays a positive effect between network size and growth, while personal network plays a more significant role in the relationship of tie strength and growth than organizational network. These results promote managers to take productive strategies for entrepreneurial enterprises’ growth. Our study provides a meta-analysis to merge different sounds about the relationship of network properties to the growth of entrepreneurial enterprises, emphasizing moderators of organizational and personal networks among these above relationships. Thus, these findings make significant contributions to the field of entrepreneurship. Keywords social network, network size, network density, tie strength, organizational network, personal network, meta-analysis members, and it may offset the incremental benefits. While Introduction Ostgaard and Birley (1996) and Batjargal (2005b) obtained a Resources obtained from social network can assist entrepre- different result, network size negatively correlates with neurs to overcome difficulties, challenges, and even survival growth. As for network density, sparse networks helped iden- (Drummond et al., 2018). Social network provides low-cost, tify entrepreneurial opportunities to capture non-repetitive fast access to resources, including information technology, information (Bhagavatula et al., 2010; J. Yang & Zhang, financial capital, physical assets, etc. (Bratkovic et al., 2009; 2015) and increase the chances of creating competitive Cantner & Stützer, 2010; Hillman & Dalziel, 2003). Social advantages. However, dense network led to redundant infor- network also provides a convenient communication channel mation (Singh et al., 2000), limited its access to a wide range between entrepreneurial enterprises and external organiza- of information, and hindered its growth and progress. Whereas, tions for timely and valuable information (Diánez-González Bhagavatula and Elfring (2010) considered dense network & Camelo-Ordaz, 2019), achieving high growth and good increased mutual benefit between venture enterprises and performance (Ge et al., 2009). other members. Cantner and Stützer (2010) believed family However, some scholars hold different views on the role of social network. Not all social networks could generate posi- Wuhan University of Technology, China tive social capital. The key is how to excavate the properties Linköping University, Sweden of social network (Bratkovic et al., 2009). A larger network University of Vaasa, Finland made it more likely to provide rich information (Singh et al., Corresponding Author: 2000) and cooperate with its suppliers, customers, and com- Yang Liu, Department of Management and Engineering, Linköping petitors (Galkina & Lundgren-Henriksson, 2017). But Hansen University, SE-581 83 Linköping, Sweden. (1995) thought a larger network made less time to keep with Email: yang.liu@liu.se Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open or friends could help entrepreneurial enterprises increase the two dimensions of personal network and organizational net- chances of success and reduce their distrust because weak ties work. So we have provided six hypotheses, trying to build a led to arbitrage on potentially high-margin ideas (Bradley framework for network type, network properties, and the et al., 2012). Bhagavatula and Elfring (2010) held opposite growth of entrepreneurial enterprises. ideas. Weak ties could increase the possibility of obtaining The contributions of this paper consist of two points. more scarce resources, reduce the redundancy of information, Firstly, this paper enriches the literature and responds to the and enhance the chances of successful entrepreneurship. calls to research the relationships between network proper- Therefore, it would be inconsistent views about the influence ties and the growth of entrepreneurial enterprises at a greater of network properties-growth relationship. depth. Secondly, we have investigated the moderator of orga- So far, some scholars have used meta-analysis to research nizational and personal networks on the network properties- the effect of some network properties on firm performance, growth relationship. but further research still exists. Stam et al. (2014) focused on The structure of this paper is as follows: In Section 2, we small firms and selected control variables for firm type, review the theories of social network and the growth of industrial type, and economical type, and the variables are entrepreneurial enterprises. Section 3 presents the basic personal network’ structural holes, strong ties, weak ties, and hypotheses of the research. Section 4 introduces the method- diversity. Rauch et al. (2016) mainly researched network ology and analytical procedure. Section 5 discusses theoreti- cohesion and diversity with control variables as firm age, cal insights and managerial implications. Finally, Section 6 firm size, industry. However, the effectiveness of entrepre- presents limitations and suggestions for future research. neurs’ personal network to entrepreneurial performance is usually measured as organizational performance, neglecting Literature Review influences of organizational network (Bratkovic et al., 2009; Stam et al., 2014). Some scholars considered social networks We review the theories of social network and the growth of individual resources (Arroteia & Hafeez, 2020), while it also entrepreneurial enterprises in four parts: the growth of entre- referred to organizational resources. Few ventures could preneurial enterprises, network properties, network types, operate successfully without the relationship between orga- and gaps identified from the literature review. nizations and other organizations (Donnell et al., 2001). Whether personal or organizational network plays a more The Growth of Entrepreneurial Enterprises significant effect on the growth of entrepreneurial enterprises should be further studied. Also, social network of entrepre- Social network can provide valuable resources that entrepre- neurial enterprises and that of entrepreneurs are not identical, neurial enterprises need to acquire, including tangible while this problem has been neglected. Both organizational resources and knowledge, advice, and emotional support and personal networks impact social networks (Donnell (Arregle et al., 2015). It can affect an entrepreneurial enter- et al., 2001), and they may influence differently on the prise’s economic performance through many channels growth of entrepreneurial enterprises. The existing research (Casson & Giusta, 2007). An entrepreneurial enterprise focused on the influence of network types on new venture could not grow well without contacting other entrepreneurs internationalization (Manolova et al., 2010), on the process or organizations (Donnell et al., 2001). If an entrepreneurial of entrepreneurship (Turner & Pennington, 2015), and enterprise wants to build a new venture, entrepreneurs or reviewed different network types (Donnell et al., 2001). It entrepreneurial teams should contact the government to needs to be further researched about the impact of network apply for new ventures’ qualifications, do relevant proce- types between network properties and the growth, and it may dures, obtain entrepreneurial policies, etc. Social network explain why there existed different ideas about the influence can give birth to entrepreneurial enterprises, and their net- of network properties on the growth of entrepreneurial enter- work properties play an important role in the growth of prises. This paper devotes itself to answering the following entrepreneurial enterprises (Fernández-Pérez et al., 2016; H. questions. (1) How do network properties (network size, net- Yang & Dess, 2007). work density, and tie strength) influence the growth of gen- Entrepreneurial enterprises often face numerous restric- eral entrepreneurial enterprises? (2) Do network types tions on access to or control over resources. Even without a (organizational and personal network) have impacts on the clear concept of the source of competitive advantage, the network properties-growth relationship? speed and probability of failure may be faster than that of We try to research the positive influence of network prop- mature enterprises. Entrepreneurs have a challenging period erties on the growth of entrepreneurial enterprises. Network to find venture capital, get governmental approval, study cus- size, network density, and tie strength are three key properties tomers etc. which all were growing venture needs in their of social network (Heirati et al., 2013; Mbura, 2015; Rooks social network (Cui et al., 2018). Social network is a crucial et al., 2014). There were also different sounds about the rela- mechanism for entrepreneurial enterprises to collect resources, tionship between network properties and the growth of entre- information, and assets. Social network required for the preneurial enterprises. While network properties also refer to growth of an entrepreneurial enterprise includes all kinds of Peng et al. 3 resources embedded in and derived from a network owned by or company’s value, entrepreneurs’ personal network pro- an individual or a social institution. It promotes entrepreneur- motes the growth of entrepreneurial enterprises in the early ial action operating well (Ndofor & Priem, 2011). It helps stage of entrepreneurship. While in the middle stage, an enter- enhance enterprises’ opportunities to obtain potential custom- prise needs to develop its partnerships network (Gu & Su, ers’ demands, new sales markets, or market segmentation. 2018) or alliance network (Goerzen, 2007) to extend its busi- The ability to obtain resources has a decisive effect on the ness, which refers to organizational network. Relatively growth of entrepreneurial enterprises (Ge et al., 2009). While speaking, inter-organizational network connects different the sources of entrepreneurial resources are largely dependent organizational networks and spans different organizations. on the supply of social network, and the environmental impact There is not a clear boundary of inter-organizational network seems to be secondary (Volpe & Biferali, 2008). (Bergenholtz & Waldstrøm, 2011). Elements of social net- work are usually people, either individuals or social units, for instance, families and clubs (Casson & Giusta, 2007). Network Properties Compared with prior research, all network types could be cat- Social network has many properties, such as network size, egorized as personal and organizational networks. network density, tie strength, etc. When Arregle et al. (2015) Personal network is sometimes called individual network, studied family ties in entrepreneurs’ social networks and new such as entrepreneurs’ network (Klyver & Christensen, 2007), venture growth, they thought network size was one of the or personal contact network (Donnell et al., 2001). The avail- most important control variables. When it comes to family ability and value of personal network could explain why ties, scholars thought tie strength was divided into strong ties some people could build a new venture and others not. and weak ties, that family ties belonged to the former ties Personal network usually helps entrepreneurs look for buyers (Jenssen & Greve, 2002). Besides, network density was and suppliers, which could promote the growth of entrepre- another valuable network control (Bahlmann, 2014; Zhou neurial enterprises (Batjargal, 2005a), for example, enter- et al., 2020). Network properties also include network diver- prises’ revenue growth. While organizational network means sity, structural holes, and network cohesion, but network a firm’s network, an entrepreneurial team and so on (Demirkan size, network density, and tie strength were the three main et al., 2013; Omri & Boujelben, 2015), it refers to an entrepre- properties. For instance, network diversity was changed by neurial team or a sub-company or different department of a adding and dropping numbers of partners to increase the firm, the tie between them may occur in an internal network. diversity of information (Demirkan et al., 2013), and it was Sub-organization is one part of organizational network, and it based on the existence of network size. The distant or non- contains joint ventures, franchise chains, strategic alliances, existent relationship between two network members is called and so on (Turner & Pennington, 2015). These styles of the structural holes closely associated with network density and new organizational network bring more advantages to tie strength (Batjargal, 2005b; Tang et al., 2020). increase original entrepreneurial enterprises. It is usually Hansen (1995) studied entrepreneurial network earlier, described as a special system that connects units, divisions, employing network size, network density, and tie strength to and networks. It plays a vital role in the growth of entrepre- describe the entrepreneurial action set variables. It was the neurial enterprises and personal networks. same with Mbura (2015) ideas that this kind of network anal- ysis could consider both social network structure and con- Hypotheses Development tent. Rooks et al. (2014) believed that social network should fall into network level and relational level, which meant the Referring to our study, we propose six hypotheses: the effects structure and content of the network. From the content of of network properties on the growth of entrepreneurial enter- their studies, that was to say, social network could be com- prises, and the moderators of personal network, organiza- posed by network size, network density, and tie strength. tional network between these two variables. Therefore, we take network size, network density, and tie As for correlation, we followed three steps: In the first step, strength as our main network properties. we put forward our idea and then explain why the positive side exists. In the second step, we explain why its opposition from its opposite side is not good. In the third step, we offer opin- Network Types ions on how the positive side influences and what benefits can According to the characteristics of a network, entrepreneurs create for the growth of entrepreneurial enterprises. may need a competitive or supportive network (Das & As for the moderator, the first and third steps are similar Goswami, 2019; Prajapati & Biswas, 2011) that refers to per- to the steps for correlation mentioned above. In the second sonal network. If we want to achieve the growth of entrepre- step, we put forward the reason for both organization net- neurial enterprises, we should focus on the enterprises’ formal work and personal network having a moderating effect on organizational structures and more individuals’ and groups’ the growth of entrepreneurial enterprises and explain why informal relationships (Hemphälä & Magnusson, 2012). the moderating effect of organization network and personal Under the status of small resources without the effect of brand network was greater. 4 SAGE Open size is limited to family and friends, relatives, government, Network Size and the Growth of Entrepreneurial and financial institutions (Das & Goswami, 2019; Prajapati Enterprises & Biswas, 2011). While organizational network that concluded Expansion of network size of social network can increase the with alliance networks could provide more firm’s competi- extent to which entrepreneurial enterprises gain access to tive activities (Chi et al., 2010), making the enterprise build resources through the network (J. Yang et al., 2011). The size its competitive network to grow fast. Thus, we proposed: of network becoming large means more contacts, and the combined amount of information every member carries will Hypothesis 2: Network size is more positively related to be multiple quantities. More network members might explore the growth of entrepreneurial enterprises in organisational more new knowledge and increase the knowledge they network than personal network. receive (Fernández-Pérez et al., 2016). Research has shown that a large network provides a greater possibility to collect Network Density and the Growth of information than a small one (Fernández-Pérez et al., 2016). Entrepreneurial Enterprises Expanding the size of social network can promote access to more quantity and quality of entrepreneurial resources, Network density measured whether the link of entrepreneur- thereby improving the efficiency of access to entrepreneurial ial enterprises is dense or sparse. When the possible contacts resources and thus achieving sustainable competitive advan- are fixed, density depends on the number of current ties. The tages (Ge et al., 2009). While with little contact with others, network density becomes great, and the number of members the quantity of information and resource brought by a net- at a certain time could contact other people is huge (H. Yang work member is limited as well as the total quantity. From & Dess, 2007). Numerous contacts may offer the necessary the upstream perspective of stakeholders, little information resources that enterprises need. An intensive network gener- about suppliers may increase the operation cost of the start- ates redundant information (Granovetter, 1973), and over- ups. From the downstream perspective of stakeholders, sel- lapping information is useless to foresee trends in products dom information about customers may lead to a tiny market and markets for entrepreneurial enterprises (H. Yang & Dess, share. All of these would result in low impeding the growth 2007). Rather than helping entrepreneurial enterprises of entrepreneurial enterprises. In fact, entrepreneurial enter- grow, it consumes resources and hinders enterprises’ growth, prises whose broad networks are more successful and may bringing fewer consumers. Sparse network provides access have a greater possibility of growth (Lamine et al., 2017). A to new, valuable information (Jenssen & Greve, 2002). large network brings more chances for entrepreneurs to Although few ties exist, people or organizations could not increase their creativity and improve their ability to imple- create a close or monopolistic network, and entrepreneurial ment innovative ideas (Fernández-Pérez et al., 2016). Thus, enterprises could seek resources without market threat. we proposed: Diverse resources from sparse network make entrepreneurial Hypothesis 1: Network size has a significant positive enterprises more likely to enter the dominant market (Ndofor effect on the growth of entrepreneurial enterprises. Personal & Priem, 2011). However, dense network tends to give rise network refers to the network of entrepreneurs, CEOs, and to exclusive rights among leaders, and it is easy to lead to managers, while organizational network refers to networks arbitrary decision-making. Although dense network helps of entrepreneurial teams and sub-organizations or coopera- form a normative network and enhances trust and coopera- tion partners, such as joint ventures and franchise chains tion among network members, the consistency of dense net- (Turner & Pennington, 2015). Both personal and organiza- work often hinders enterprise creativity that is harmful to the tional networks provide the possibility of members’ contact, development of enterprises (H. Yang & Dess, 2007), reduces while their effectiveness may go through different ways in the probability of effective information appearing, and an entrepreneurial enterprise. From the perspective of quan- restrains the growth of entrepreneurial enterprises (H. Yang tity, organizational network may produce much more con- & Dess, 2007). Thus, we proposed: tacts than personal network. A firm with a larger size of the alliance network could help itself get access to more Hypothesis 3: Network density has a significant negative resources (Milanov & Fernhaber, 2009), including resources impact on the growth of entrepreneurial enterprises. from sectors, suppliers, or alliances. Organizational network Based on the above hypothesis, personal network’s density can help the firm to connect with buyers (R. P. Lee et al., impacts more positively on the growth of entrepreneurial 2011), suppliers (Bergenholtz & Waldstrøm, 2011), and part- enterprises than organizational network’s density does. From ners (Goerzen, 2007; Karamanos, 2012). Although personal the perspective of stakeholders theory, personal network refers network can also get in touch with some buyers, it gives buy- to entrepreneurs’ close ties such as friends and family (Jenssen ers smaller trust than organizational network. The status and & Greve, 2002), and their current ties provide a dense net- reputation of organizational network may bring more coop- work. Such a tight network tends to weaken employees’ eration and market share. To some extent, personal network’s Peng et al. 5 enthusiasm for work, which is not conducive to the growth of Then, it can help member enterprises improve the results of entrepreneurial enterprises. While organizational network risk identification, reduce the probability of failure and pro- refers to an enterprise’s external network that could bring the mote an increase in entrepreneurial income (J. Yang & chance of cooperation with customers, suppliers, government, Zhang, 2015). and competitors. Too tight ties between organization networks are likely to bring unfair competition or increase the depen- Hypothesis 5: Tie strength has a significant positive dence of the entrepreneurial enterprise on the other organiza- impact on the growth of entrepreneurial enterprises. tions, but on the contrary, weaken their competitive advantages and bargaining power. Personal network in dense network Based on the above hypothesis, personal network’s tie bringing overlap and obsolete information tends to be a barrier strength impacts more positively on the growth of entrepre- to entry of new information (Prajapati & Biswas, 2011), while neurial enterprises than organizational network does. organizational network being dense may enhance the degree Personal network’s closest relationship among members of barrier existing, for a reason that dense network causes the could operate their network to tap into the advice network enterprise’s operations transparent which may lead itself to be (Manolova et al., 2010). Advice network often occurs in passive for product pricing or profit capture. Sparse personal mutual trust among network members, through intimate, network could bring more different information for enter- long-time, and frequent communication. That is to say, tie prise’s innovation and development, as well as sparse organi- strength could help offer more believable advice. In a limited zational network. There exist many personality differences amount of time, organizational network may tend to be weak among network links in organizational network (Turner & ties, and it may take much more time to keep up with organi- Pennington, 2015). Differences are bigger than personal net- zational network’s members than personal’s (Hansen, 1995). works’. Dense network is easier to overlap information (Singh Personal network tends to be direct ties with network mem- et al., 2000), organizational network can mitigate this overlap. bers, and they may have known each other before. It increases Through organizational network, entrepreneurs could catch the trust of network links, can enhance interaction with net- opportunities easily in sparse network (Batjargal, 2005b). work members, and is easy for entrepreneurs to build emo- Thus, we proposed: tions with them in a short time (Bratkovic et al., 2009). However, organizational network always represents its Hypothesis 4: Network density is more negatively related enterprise to contact buyers, suppliers, government, banks, to the growth of entrepreneurial enterprises in organisa- or others, before it gets the brand’s effectiveness. It might be tional network than personal network. hard to get trust with them getting commercial transactions from a new organization. While personal network has been most frequently employed in a newly created firm, personal Tie Strength and the Growth of Entrepreneurial network based on entrepreneurs’ egocentric network that Enterprises provides advice could serve as an informal safeguard against potential opportunistic behaviours from mutual acquaintances Many scholars believe that tie strength is necessary for the (Mahmood et al., 2011), compared with organizational net- acquisition and growth of early resources in the primary work, it could save more time, money, resources, or other period of establishing an enterprise. Strong ties make enter- energies in information search. Thus, we proposed: prises expand the market or purchase fixed assets (Ge et al., 2009). They come from the closest circle of friends and fam- Hypothesis 6: Tie strength is more positively related to ily members (Cantner & Stützer, 2010), bring higher emo- the growth of entrepreneurial enterprises in personal net- tional intensity and closer ties (Zhang & Cao, 2007), and work than organisational network. promote the identification, development, and utilization of information (J. Yang & Zhang, 2015). Repeated collabora- tion gives entrepreneurs closer trust (J. Yang & Zhang, 2015) Conceptual Model and enhances potential cooperation (Demirkan et al., 2013), which reduces the cost of information assessment and vali- As mentioned above, we could propose a conceptual model, dation. While weak ties weaken connections between mem- as shown in Figure 1. (we employ Visio software to create bers, there is no trust among companions. How to complete the artwork throughout our study). Both network size and tie production transaction and profit distribution have become a strength are positively related to the growth of entrepreneur- controversial problem. Conflicts between interest subjects ial enterprises. Network density is significantly negative for will affect the growth of entrepreneurial enterprises. Closer growth. The relationship between network size and growth is trust has many additional functions. First, it can enhance stronger for organizational network and network density. information exchange and integration; promote close com- While the relationship between tie strength and growth is munication and mutual learning among network members. stronger for personal network. 6 SAGE Open Figure 1. Conceptual model. Rauch et al. (2016) for the study. We used combinations of Methods keywords related to network size (e.g., the size of network, This study employs meta-analysis to research the relationship network size, network range, and network scale), network between social network and the growth of entrepreneurial density (e.g., the density of network and network density), enterprises. We used the meta-analytic approach for two rea- tie strength (e.g., network strength and tie strength), and the sons. Firstly, there are different sounds about the relationship growth of entrepreneurial enterprises (e.g., firm growth, of social network to the growth of entrepreneurial enterprises sale growth, and profit growth). By reading through down- based on the sight of network type. While meta-analysis is a loaded references, we got the definitions and measurement tool of merger statistics, it can be used to aggregate and pro- indicators of previously selected keywords, expanded the cess independent research results with the same research range of keywords combined, and searched databases again objective (Bierwerth et al., 2015; Schwens et al., 2018; Stam until there were no new related references. The search et al., 2014; Zhao et al., 2021). The meta-analytic approach terms help us to collect a number of references and to can evaluate the total correlation between variables and offer collect a number of references and understand the relation- us the size of variables’ relationship. Secondly, the meta-ana- ship between social network attributes and the growth of lytic approach has been widely applied in the field of entre- entrepreneurial enterprises. preneurship research by many scholars. It is a new Then we set five steps to get related empirical articles that comprehensive literature analysis method combining qualita- we need. Firstly, we searched official databases: Elsevier tive and quantitative analysis (Bierwerth et al., 2015; Schwens Science Direct, Web of Science, Google Scholar, EBSCOhost, et al., 2018; Stam et al., 2014; Zhao et al., 2021). Through the JSTOR, and Psyclnfo by combining keywords (Mrabet & secondary analysis of the existing research data, combined Ellouze, 2014). Secondly, we manually went through the with the existing development environment and situation, principal entrepreneurship, management, and business jour- effective suggestions and solutions suitable for modern devel- nals, such as Small Business Economics, Entrepreneurship opment can be obtained. In addition, the number of hypothe- Theory and Practice, Academy of Management Journal, and ses does not influence the application of the meta-analytic Academy of Management Review. This step aims to supple- approach. There were more than six hypotheses in the previ- ment the scope of reference retrieval and make the retrieval ous study by Stam et al. (2014) and Rauch et al. (2016). Their more comprehensive. Because some studies may be unpub- studies also focused on firm performance. As for our study, lished in UTD and FT, but they were already online. And we we set two steps. At first, we define search strategy and inclu- were searching the selected journals for other cited articles sion criteria, including network size, network density, tie that may be helpful. Thirdly, we searched databases of SSRN, strength, and the growth of entrepreneurial enterprises. Then, conference proceedings of the Academy of Management and we describe meta-analytic procedures and illustrate selected Babson College Entrepreneurship Research Conference, data that we need to calculate. searching for unpublished literature to reduce publication bias. Fourthly, we used the correlation coefficient to respond to effect sizes of network properties, network types, and the Search Strategy and Inclusion Criteria growth of entrepreneurial enterprises. This paper tries to use First of all, we need to define search strategy and inclusion the harmonic average, and the algorithm has been exten- criteria. We followed the idea of Stam et al. (2014) and sively used in the field of entrepreneurship (Rosenbusch Peng et al. 7 Table 1. Literature Screening Results. Organizational Personal Pieces of Total Relationship between variables network (ON) network (PN) reference samples Network size to the growth of entrepreneurial enterprises (SG) 8 10 18 2,975 Network density to the growth of entrepreneurial enterprises (DG) 3 3 6 1,158 Tie strength to the growth of entrepreneurial enterprises (TG) 11 18 29 5,119 Records identified through database Additional records identified retrieving (n=821) through other sources (n=65) Duplicated articles removed Articles excluded based on initial (n=833) screen (n=383) Excluded due irrelevant to Title and abstracts screeded (n=450) entrepreneurship (n=233) Excluded due effect sizes Full-text articles assessed for inconsistent with requirement eligibility (n=217) (n=189) Studies included in quantitiative synthesis(meta-analysis) (n=28) Figure 2. Flow chart of the references search process. et al., 2013; Schwens et al., 2018). Fifthly, if two or more Clark (2003), network range meant the different connections references were used for the same samples, we chose the ear- or network diversity. lier one. If a reference reported multiple independent sam- Network size. It reflects the number of relationships indi- ples, we code them several times. Finally, we got 28 viduals maintain in the social network or organization they quantitative empirical articles containing 31 independent did business with (Prajapati & Biswas, 2011; Premaratne, samples with 5,259 observations shown in Table 1, and the 2002). We can measure it by calculating the total number of retrieval process was illustrated in Figure 2. possible contacts. We used the following keywords: network We mainly searched keywords according to the following size (Batjargal et al., 2013; Scholten, 2006), network range criteria. At first, we searched the selected combined key- (Ge et al., 2009), network scale (J. Yang et al., 2011), breadth words such as network size and the growth of entrepreneurial of external communication and number of partners (D. Y. enterprise. We ensure the definition and measurement by Lee & Tsang, 2001), etc. It should note that network range reading the selected journals. And then, we explicitly include represented the different connections or network diversity and exclude keywords by reading their definition and mea- (Collins & Clark, 2003), while network size indicated the surement carefully. For example, when we searched data on number of connections(Batjargal et al., 2013). network size to the growth of entrepreneurial enterprises, we used network range to search for related network size refer- Network density. It is a proportion of identified contacts ences. In reference Ge et al. (2009), network range meant the present out of the total possible contacts (Premaratne, number of network members, while in reference Collins and 2002). We can measure it by calculating the total number 8 SAGE Open of identified contacts divided by the total possible numbers growth, market share growth, employ/employment growth, of network members, while the total number of possible ties organization growth, and stock growth. Secondly, taking equals network size. So network density ranges from 0.0 to the growth rate to measure venture/firm growth, such as 1.0. It tended to measure the collective social capital avail- sales and profit growth rates. Thirdly, employing growth able to all members of the network, which could be divided speed, sales growth speed, new employees increase speed, into sparse and close networks (Ge et al., 2009). Meanwhile, market share growth speed, and net earnings growth speed. it was measured by the degree to which social networks are Fourthly, when referring to the growth, scholars collected closely connected (Hoang & Antoncic, 2003). When the data by collecting a new venture’s first year’s performance, network density was relatively high, all network members such as first year and first 5 years. Fifthly, entrepreneurship communicated and interacted with each other (Liu et al., performance was measured in the venture-growth stage. 2009). The main keywords found in the retrieving process To improve coding reliability, the first and second authors were as follows: density (Bhagavatula et al., 2010; Prajapati both coded the studies. Characteristics of 28 quantitative & Biswas, 2011; Scholten, 2006), network density (Batjargal empirical articles are shown in Table 2. et al., 2013; Scholten, 2006), degree (Hansen, 1995). Meta-Analytic Procedures Tie strength. It is measured by the duration of the relation- ship, the intimacy of the relationship, the frequency of com- First, we test whether we could research by meta-analysis. munication, etc. (Ge et al., 2009; Jenssen & Greve, 2002). We follow the research role of meta-analysis. No less than 20 Tie strength was related to the communication time and the documents are recommended for inclusion in the analysis. degree of emotional intimacy and mutual trust of the mem- No less than three papers for single group inclusion analysis bers of the network (J. Yang et al., 2011). Tie strength usually of combinatorial meta-analysis are used as criteria. We test comes from the closest circle of friends and family members the statistical heterogeneity of the study with Q statistics. (Cantner & Stützer, 2010), which refers to the direct ties, After that, we quantise it with I-squared (I ) to test the effects including trust, reciprocity, embedding, etc. (Granovetter, of heterogeneity among studies. If p-values (p1) < .05, 2 2 1973; Scholten, 2006). We used keywords as follows: net- I > 50%, indicating that there is heterogeneity (I > 75%, work strength (J. Yang et al., 2011), network intensity (Brat- the extent of heterogeneity is high), the random effect model kovic et al., 2009; Ge et al., 2009), tie strength (Musteen is selected. On the contrary, the fixed-effect model is selected et al., 2013; Scholten, 2006) etc. We excluded descriptions (Stam et al., 2014). However, if p-values (p1) < .05, I < 50%, about weak ties among tie strength. indicating a low heterogeneity among studies. That is to say, the research result of these variables is consistent. Organizational and personal network. As for personal net- Since publication bias may be a serious problem in the work, we chose keywords including CEOs’ external social meta-analysis (Schwens et al., 2018), we use Duval and network (Fernández-Pérez et al., 2016; Musteen et al., 2010), Tweedie’s trim and fill tests, Begg and Mazumdar test, and employees’ network (Hemphälä & Magnusson, 2012), firm Egger test to test the potential publication bias, in which Duval owners’ network (Manev et al., 2005), and entrepreneur’s and Tweedie’s trim and fill tests need to be adjusted to achieve network (Klyver & Christensen, 2007). As for organiza- symmetry in the funnel plot. The funnel graph is not symmet- tional network, we chose keywords including firms’ initial ric, indicating that the difference between observed and networks (Demirkan et al., 2013), entrepreneurial team’s adjusted values is more than 0.1 (i.e., Δr > .1). The Egger test network (Omri & Boujelben, 2015), a network in collectiv- uses the slope of the regression line to represent the normaliza- istic context (Rooks et al., 2014), external partnerships (Gu tion effect, and the regression intercept value is significant & Su, 2018). Following with ideas of Turner and Pennington (i.e., p2 > .1). Begg Mazumdar test uses the level correlation (2015), organizational network also contained alliance net- between the effect size and the standard error, and the rank works (Rowley et al., 2000), and cluster ties (Li et al., 2013). correlation is significant (i.e., p3 < .1). Only when all results of the three tests meet the above values, indicate the existence The growth of entrepreneurial enterprises. The success of publication bias that this study is considered to have a seri- of entrepreneurial enterprises can be measured by survival ous impact on publication bias (Schwens et al., 2018). and growth (Semrau & Werner, 2014), while survival tends to be a minimum criterion of success. Growth is a vital Results entrepreneurship performance outcome because it confers entrepreneurial enterprises with increased abilities, powers, First, the heterogeneity test results showed that the p-value and profits (Vissa & Chacar, 2005). Prior studies referred of the relationship between three network properties and the to five ways to measure it. They are, firstly, conceptual- growth of entrepreneurial enterprises was less than .01. izing related indicator growth, such as sales growth, profit Results of all organizational network properties to the growth Peng et al. 9 Table 2. Independent Samples. Publication Type of social Number Authors (year) N Countries status SG DG TG network Construct labels 1 Arregle et al. 515 China, Russia, Pub .107 .073 PN Network size, family ties, and (2015) France, and revenue growth America 2 Batjargal (2000) 75 Russia Unpub .110 .000 PN Network size, strong ties, and sales growth 3 Batjargal 159 China and Unpub −.050 .085 −.215 PN Network size, network density, (2005a) Russia tie strength, and revenue growth 4 Batjargal 56 Russia Pub .090 PN Network size and revenue (2005b) growth 5 Batjargal et al. 637 China, Russia, Pub .060 −.170 −.020 PN Network size, network (2013) France, and density, family ties, and America revenue growth 6 Bradley et al. 201 Dominica Pub −.090 PN Strong ties and profit growth (2012) and Kenya 7 Bratkovic et al. 103 Slovenia Pub .107 PN Resource network (2009) intensity + central network person contact + central network person friendship and sales growth 8 Cantner and 182 Germany Pub −.090 PN Strong ties and employee Stützer (2010) growth 274 Germany .030 ON 9 Castro et al. 126 Colombia Pub .064 .102 ON Network size, strong ties, (2014) andrevenue growth 10 Collins and 73 America Pub .190 .155 ON External network + internal Clark (2003) network size, external network strength of ties, and sales growth + stock growth 11 Danis et al. 117 Hungary Pub .260 ON Networking intensity and (2010) sales growth + revenue 182 Hungary Pub .010 ON growth + employee growth 12 Ge et al. (2009) 177 China Pub .071 .183 ON Network range, network intensity, and revenue growth + sales growth + employee growth 13 Hansen (1995) 44 America Pub .530 .480 −.080 ON Network size, network density, frequency, and organization growth 14 Gu and Su 177 China Pub .071 .183 ON Network range, network (2018) intensity, and sales growth + employment growth + market share growth 15 Jones and 211 England Pub .220 PN Strong ties and sales Jayawarna growth + turnover growth (2010) 16 D. Y. Lee and 168 Singapore Pub .191 .280 PN Number of partners + breadth Tsang (2001) of external communication, frequency of external communication, and venture growth 17 Manev et al. 160 Bulgaria Pub .100 PN Strong ties and employee (2005) growth 18 Musteen et al. 169 Czech Pub .140 .180 PN International network density, (2013) international network tie strength, and sales growth (continued) 10 SAGE Open Table 2. (continued) Publication Type of social Number Authors (year) N Countries status SG DG TG network Construct labels 19 Ostgaard and 159 England Pub −.024 −.080 PN Size of networks, the Birley (1996) intensity of relationship of personal networks, and sales growth + profit growth + employment growth 20 Sawyerr et al. 153 America Pub .127 .177 PN Frequency and number of (2003) contacts and sales growth 21 Scholten (2006) 65 Holland Unpub .170 −.050 −.090 ON Network size, tie strength, network density, and employee growth 22 Semrau and 146 Germany Pub .095 .065 PN Network size, tie strength, Sigmund and revenue growth + profit (2012) growth + employment growth 23 Vissa and 84 India Pub .250 −.340 ON Network size, network Chacar (2005) density, and revenue growth 24 J. Yang et al. 130 China Unpub .629 .606 PN Network scale, network (2011) strength, and net earnings growth + sales growth + employees growth + market share growth 25 Zhang and Cao 91 China Pub .248 ON Tie strength and sale (2007) growth + profit growth + market share growth + employees growth 26 X. Zhao et al. 133 China Pub .233 −.060 PN Business network (2010) size + government network size and employee growth + business growth 75 China .318 .310 PN Business network size + government network size and asset growth + business growth 27 L. Zhao and 210 China Pub .364 PN Strong ties and fast growth Ha-Brookshire (2018) 28 Zou et al. 252 China Pub .000 PN Strong ties and organic (2010) growth + partnership growth + acquisition growth Note. Pub = published; Unpub = unpublished; PN = personal network; ON = organizational network. in I were less than 50%. Most scholars’ current views on by Stam et al. (2014). The paper analyzed the significance organizational network were consistent. I of personal net- of the relationship between social network and the growth of work and overall network were almost closest to 75%, so entrepreneurial enterprises. Also, social network would be there exists high heterogeneous between these variables. more positively related to the growth of entrepreneurial From Table 3, all results indicated that there was no obvi- enterprises in personal network than organizational network ous publication bias. (r = .097 < r = .129, p = .000 < .001, p = .002 < .01). og pg og pg Next, we assessed the impact of network size, network Network size and tie strength had a positively significant density, and tie strength on the growth of entrepreneurial impact on the growth of entrepreneurial enterprises enterprises. The overall relationship between the social net- (r = .164 > 0, p < .001; r = .100 > 0, p = .002 < .01), sg sg tg tg work and the growth of entrepreneurial enterprises was pos- while network density had no significant negative effect on itively significant (r = .115, p < .001), it was recognized the growth of entrepreneurial enterprises (p = .901 > .1). ng ng dg Peng et al. 11 Table 3. The results of comparative analysis. Trim and fill Egger B&M Variable k N r 95% CI p1 I ik Δr p2 p3 NG (network-growth) 31 5,259 .115 [0.057,0.172] .000 76.467 9 .081 .070 .122 ON-growth (OG) 14 1,573 .097 [0.050,0.143] .000 49.020 3 .030 .066 .171 PN-growth (PG 19 3,712 .129 [0.047,0.210] .002 83.423 0 .000 .127 .363 SG-growth (SG) 18 2,975 .164 [0.086,0.240] .000 75.845 6 .086 .114 .049 ON-SG-growth (OSG) 8 777 .174 [0.104,0.243] .000 0.075 3 .041 .062 .386 PN-SG-growth (PSG) 10 2,198 .146 [0.029,0.259] .014 85.300 0 .000 .400 .531 DG-growth (DG) 6 1,158 .012 [-0.176,0.199] .901 87.070 1 .085 .275 .452 ON-DG-growth (ODG) 3 193 .029 [-0.420,0.467] .904 90.451 2 .369 .005 .296 PN-DG-growth (PDG) 3 965 .010 [-0.205,0.224] .928 88.680 2 .180 .100 .602 TG-growth (TG) 29 5,119 .100 [0.037,0.162] .002 79.731 5 .061 .286 .311 ON-TG-growth (OTG) 11 1,281 .077 [0.005,0.149] .037 45.917 0 .000 .737 .697 PN-TG-growth (PTG) 18 3,656 .132 [0.041,0.220] .004 86.324 4 .081 .250 .596 Note. k = the number of samples; N = the number of observations; r = weighted mean observed correlations; 95% CI = 95% confidence interval; p1 = the p-value of test about variables; I = the I-squared of heterogeneity test; ik = the number of studies trimmed; Δr = difference between observed values and adjusted values; p2 = the p-value of Egger’s regression intercept test; p3 = the p-value of Begg and Mazumdar rank correlation test. Hypothesis 1 and Hypothesis 5 were accepted, while Table 4. The Results of Hypotheses. Hypothesis 3 and Hypothesis 4 were rejected. Hypotheses Results Hypotheses Results Finally, network size was more significantly positive related to the growth of entrepreneurial enterprises in organi- H1 Supported H4 Not supported zational network than personal network (r = .174 > r = .146, H2 Supported H5 Supported osg psg p < .001, p = .014 < .05), tie strength was more signifi- H3 Not supported H6 Supported osg psg cantly and positively related to the growth of entrepreneurial enterprises in personal network than organizational network strangers to join them. Keeping a large network leads to an (r = .077 < r = .132, p = .037 < .01, p = .004 < .01). otg ptg otg ptg increased potential for goal and value conflicts among addi- Hypothesis 2 and Hypothesis 6 were supported. tional network members, and it is challenging to manage effectively (Demirkan et al., 2013). Therefore, there might Discussion be a threshold of network size for the growth of entrepre- In the end, we obtained these results shown in Table 4. neurial enterprises. When it exceeds this threshold, network From Hypothesis 1, we find that the impact of network size would weaken the effect on the growth and even hinder size on the growth of entrepreneurial enterprises is signifi- entrepreneurial enterprises’ growth. Network size extending cant positively. This is in line with the many views of the under this threshold can promote growth significantly. academic community. Fernández-Pérez et al. (2016), Diánez- Besides, the expansion of network size is the increase in the González and Camelo-Ordaz (2019), Sullivan and Marvel network members and the quality. (2011), and others believed that network size determined the From Hypothesis 2, we find that organizational network scope of activities of entrepreneurs or entrepreneurial enter- enhances the influence of network size on the growth of prises, and it was consistent with the research results of entrepreneurial enterprises is larger significant positively Milanov and Fernhaber (2009), R. P. Lee et al. (2011), and than personal network. A larger network contained more Bergenholtz and Waldstrøm (2011). A larger network opens information about the top management team’s organizations the possibility of more information and resources for entre- (Collins & Clark, 2003). Three years after start-up, entrepre- preneurial enterprises. However, it contradicted the results of neurs should expand their network size into developing busi- Hansen (1995) because every time a network member was nesses (Ostgaard & Birley, 1996). Organizational networks added to the social network, the overall benefit of the enter- include many types of relationships, such as strategic part- prise would be reduced. When an entrepreneur builds a firm, ners, suppliers, and customers. A larger network size made a larger network will not promote growth in the first 3 years other customers believe that the current firm might create (Batjargal, 2005a). A network with a low rate of strangers more possibilities for benefits (R. P. Lee et al., 2011). tended to enhance the growth (Ostgaard & Birley, 1996), and Besides, organizational network likes to build alliances to entrepreneurs expanding their network may attract more increase the enterprises’ performance (Raz & Gloor, 2007). 12 SAGE Open While some scholars might hold different ideas (D. Y. Lee & of strengthening their networks (X. Zhao et al., 2010), it Tsang, 2001; Musteen et al., 2010). An entrepreneurial enter- constrained enterprises’ development (Castro et al., 2014). prise with many founders may have higher opportunities of Maintaining tie strength costs much time and money it succeeding (D. Y. Lee & Tsang, 2001), and cooperation with reduces current assets and strains the capacity of growing other partners is only for entrepreneurs’ charisma. But per- businesses. We believed that tie strength also has a thresh- sonal network may produce contradictions among arbitrary old to enhance the growth of entrepreneurial enterprises. decisions, for example, it may occur complacency, and some From Hypothesis 6, personal network increasing the util- information spots could hinder the development of entrepre- ity of tie strength in the growth of entrepreneurial enterprises neurial enterprises (Musteen et al., 2010). is larger and significantly positive than organizational net- From Hypothesis 3 and Hypothesis 4, it indicated that net- work. It was the same with the view of many scholars. Many work density does not correlate with the growth of entrepre- scholars researched personal network’s properties, and either neurial enterprises. This conflicts with the ideas of Batjargal in a personal network or an organizational network, tie et al. (2013), Scholten (2006), etc. Comparing with these strength had a significant positive correlation to the growth. studies, differences may come from structural holes embed- Strong ties helped to obtain much trust among members con- ded into social network. Musteen et al. (2013) took structural taining suppliers and customers (J. Yang & Zhang, 2015). holes into the attribute of network density and thought that Personal network was often closely linked to acquaintances, network density reflected structural holes to a certain extent: families, and friends which were usually considered a strong High density, few structural holes. Different structural holes tie (Rooks et al., 2014). Ties in an open network were related may be in the same density network. There was a stronger to different organizations from each other (Assudani, 2009). possibility in a sparse network with many structural holes that An open network was usually along with weak ties (Mahmood provided more heterogeneous information (Scholten, 2006). et al., 2011) that led the entrepreneurial enterprise to grow As for scholars Batjargal (2005b) and Das and Goswami slowly. Based on personal network, advice sharing relied on (2019), network centrality, network heterogeneity, or struc- trust among entrepreneurs’ closely individual network, tural holes were embedded into social network, and they posi- which would decrease the cost of information acquisition tively affected the function of network density to promote the (Manolova et al., 2010). Information travelled faster through growth of entrepreneurial enterprises. It would be some influ- personal network, and it was easier for a person to identify ences between network density and centrality, heterogeneity, the valuable and potential suppliers or customers or linkers and structural holes. They all contribute to diverse informa- than an organization to do, and then take time and energy to tion and resources. From scholar Batjargal (2005b) and his catch this relationship to apply for creating values. team’s two studies, they concluded two different results. The literature in 2005 held that network density positively corre- Practical Implications lated the growth, while the literature in 2013 held the opposite. Compared with the different results, maybe family ties and From a practical point of view, our research has two consid- internal ties easily tend to tie strength that influences the func- erable implications for managers. These measures are as tion of network density to the growth. We forecast that tie follows: strength may affect the relation between network density and First, the network size has a positive and significant cor- the growth of entrepreneurial enterprises. relation with the growth of entrepreneurial enterprises, and From Hypothesis 5, tie strength encourages the growth organizational network plays a positive moderator between of entrepreneurial enterprises significantly. Extensive inter- social network and the growth of entrepreneurial enterprises. action and high trust were conducive to obtaining suffi- There exists a threshold of network size when considering its cient, accurate, timely, and useful information (J. Yang & effect on the growth of entrepreneurial enterprises. In the Zhang, 2015), beneficial to developing enterprises’ prod- early stage of entrepreneurship, entrepreneurs should take ucts (Scholten, 2006). However, some scholars held the measures to expand their network size. Managers can allow opposite view (Bradley et al., 2012; Mahmood et al., 2011; employers to participate in other activities to know more peo- Ostgaard & Birley, 1996; Raz & Gloor, 2007; X. Zhao ple who may become potential buyers, suppliers, or partners. et al., 2010). Bradley et al. (2012) believed that the infor- Then, managers should divide all network relationships into mation exchanged with friends and relatives overlapped different groups, such as new or old relationships. Besides, with the information obtained in other ways, and overlap- managers should hold annual meetings, thank customer meet- ping information raised the cost of its acquirement. ings, and competitive promotions. They should participate Traditional methods by family and friends also reduced the in investment conferences to obtain innovative ideas and get sensitivity of entrepreneurial enterprises to innovation dis- in touch with different partners. Afterwards, they could set up covery (Bradley et al., 2012). Entrepreneurs preferred to an access system to allow external organizations to register take much time and money to contact others to obtain val- for regular business exchanges. Finally, they should partici- ues, while this connecting cost would counteract the values pate in various activities organized by different external Peng et al. 13 organizations and then identify potential buyers or suppliers properties to the growth of entrepreneurial enterprises, yet to establish regular visiting relationships. the other network (centrality, network heterogeneity, and Second, tie strength has a significant positive impact on structural holes.) are still not researched. Secondly, how net- the growth of entrepreneurial enterprises. Tie strength will be work properties influence each other also deserves research. more positively significant to the growth of entrepreneurial Given the limitation of our study, the future research enterprise in personal network than organizational network. scope includes: to conduct a similar study to explore the rela- There exists a threshold of tie strength when being given tionship among centrality, network heterogeneity, and struc- influence on the growth of entrepreneurial enterprises. In the tural holes, to explore the characteristics and mutual influence first stage, entrepreneurs should adopt measures to enhance between the properties, especially tie strength and network tie strength, and in the second stage, entrepreneurs should density. take ideas to get sparse networks to get much diverse infor- mation and resources. Managers should take certain mea- Declaration of Conflicting Interests sures to make network size large when in the early of The author(s) declared no potential conflicts of interest with respect entrepreneurship and utilize personal network’s function to to the research, authorship, and/or publication of this article. strengthen its tie strength to enhance entrepreneurial enter- prises’ growth. When in the growth of entrepreneurship, Funding managers should keep the current tie strength and dig the The author(s) disclosed receipt of the following financial support potential value of weak ties. At first, managers should permit for the research, authorship, and/or publication of this article: This network members to contact members’ individual networks research was funded by the National Social Science Project and keep all network members informed of the progress of Foundation (20FGLB007). projects or other activities in each department. They should also offer extra fees for network members to regularly visit ORCID iD existing and potential contacts, such as their indirect and Yang Liu https://orcid.org/0000-0001-8006-3236 direct friends. Next, managers should work closely with employees. Every employee is required to turn in a weekly report to the head of the department, letting the head know References their behaviour every day. Afterwards, managers should reg- Arregle, J. L., Batjargal, B., Hitt, M. A., Webb, J. W., Miller, T., ularly hold monthly meetings where the department head can & Tsui, A. S. (2015). Family ties in entrepreneurs’ social net- report monthly work and share information or resources to works and new venture growth. Entrepreneurship: Theory and deepen their relationship through activities. Besides, manag- Practice, 39(2), 313–344. https://doi.org/10.1111/etap.12044 ers should know the cost of developing tie strengths and Arroteia, N., & Hafeez, K. (2020). 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SAGE Open – SAGE

Published: Jun 27, 2022

Keywords: social network; network size; network density; tie strength; organizational network; personal network; meta-analysis

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How Social Network Influences the Growth of Entrepreneurial Enterprises: Perspective on Organizational and Personal Network

How Social Network Influences the Growth of Entrepreneurial Enterprises: Perspective on Organizational and Personal Network

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How Social Network Influences the Growth of Entrepreneurial Enterprises: Perspective on Organizational and Personal Network

How Social Network Influences the Growth of Entrepreneurial Enterprises: Perspective on Organizational and Personal Network

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