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The impact of networking on bank financing: the case of small and medium-sized enterprises in Vietnam.

It is argued that networking is crucial for small and medium-sized enterprises (SMEs), particularly in emerging economies as they seek to access resources for development. One key resource in emerging economies is bank financing. In this paper, we develop a model that examines the net effect of different network ties on bank financing to private SMEs. The results support our hypothesis that different network ties influence SMEs' use of bank loans in different ways. Specifically, networking with customers and government officials promotes the use of bank loans, while networking with suppliers and social ties reduces the need for bank loans. This study provides a number of research and managerial implications, which are discussed at the end of the paper.

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Entrepreneurship has been an engine of sustained economic expansion in both developed and emerging economies (e.g., Baumol, 2002; Peng, 2001; Smallbone & Welter, 2001; Thornton, 1999). One critical success factor for entrepreneurial firms is gaining sufficient access to external sources of finance (Ahlstrom & Bruton, 2006; Le, Venkatesh, & Nguyen, 2006). This is particularly true in emerging economies because such resources are severely constrained. For example, capital markets, venture capital, and angel investors are typically at nascent stages of development. As such, bank loans tend to be the only significant formal sources of external funding for private small and medium-sized enterprises (SMEs) in emerging economies. Therefore, a key challenge for many entrepreneurs is to find a means of accessing bank loans efficiently.

From the perspective of commercial banks, lending to SMEs is perceived to be risky. But such lending is even more challenging for banks in emerging economies because the institutional environment is less developed. Banks rely on stable market institutions such as auditable business information with predictable rule of law that is enforceable to ensure repayment of their loans in some form (Nguyen, Le, & Freeman, 2006; O'Connor, 2000). Institutional stability and predictability reduces risks and uncertainty, and enhances the probability of loan success (that the principal and interest on the loan will be paid back, in full, and on time). Such market institutions, however, are often absent in emerging economies (Ahlstrom & Bruton, 2006; Nguyen, Weinstein, & Meyer, 2005; Peng, 2003). In these countries, uncertain property rights, vague laws and unpredictable law enforcement, and unavailable business data all combine to reduce the ability for local banks to emulate the practices applied by banks in developed countries. As a result, banks in emerging economies have to adjust, or rely on different lending practices (O'Connor).

If banks in emerging economies apply different lending practices, then firms borrowing from these banks also need to tailor their practices accordingly. However, empirical studies of SME bank financing in emerging economies are sparse (Cook, 2001). Instead, most studies on bank financing of SMEs examine firms in business environments that have clear property rights, as well as developed market and regulatory infrastructures, which are often less robust or almost absent in emerging economies (Ahlstrom & Bruton, 2006; Nguyen et al., 2005; Peng, 2003).

In emerging economies, personal relationships and networks are often seen as an effective substitution for well-established institutions (Ahlstrom & Bruton, 2006; Xin & Pearce, 1996). A number of studies suggest that networking between entrepreneurs, bankers, government officials, and friends and relatives may play an important role in helping both lending institutions and corporate borrowers (Ahlstrom & Bruton; Le et al., 2006; Peng, 2001; Peng & Luo, 2000). For lending institutions, networking helps them obtain information, locate markets, and better secure their investments (Le et al.; Nguyen et al., 2006). For corporate borrowers, networks are a vehicle by which they can gain access to resources, information, and support from other parties (Hoang & Antoncic, 2003).

Thus, networking could be expected to provide to the banks information on legitimacy, which in turn should give the SMEs advantages in accessing commercial bank loans. But on the other hand, one of the greatest criticisms of banking in emerging economies is that they too often rely on networking, which results in inefficient decisions in which large amounts of loans are typically never repaid (Garcia-Herrero, Gavila, & Santabarbara, 2006; Setser, 2006). Thus, it is not clear what the net effect is of different network ties on SMEs and bank loans.

This article examines the relative effect of different network ties in helping private SMEs access bank loans. This line of research is important to academics, policy makers, and managers alike, as it contributes to the understanding of SMEs and networks, and why certain types of networks seem more important for SMEs than others in accessing bank loans. We develop a model that links different types of network ties with the use of bank loans, and report an empirical test of that model in Vietnam's emerging economy. Contemporary Vietnam represents a good context for this study, with a pronounced form of entrepreneurship that operates in the virtual absence of well-established market institutions. Different network ties are extensively exploited by both banks and SMEs, allowing us to distinguish their relative importance in accessing bank financing.

In the following section, we briefly discuss institutional theory as it relates to networks and external debt financing for SMEs in emerging economies. We then develop hypotheses on the influence of different network ties for bank financing. Next, we describe our research methodology and report the results. A discussion of the theoretical and managerial implications of these findings concludes the article.

Institutional Theory, Networks, and External Debt Financing

Institutional Theory

The central premise of institutional theory is that organizations adopt structures and practices that are "isomorphic" to established organizations or professions as a result of their quest for legitimacy. Legitimacy serves as the "anchor-point of a vastly expanded theoretical apparatus" (Suchman, 1995, p. 571). It refers to the extent that key stakeholders, the general public, key opinion leaders, and/or government officials are cognizant of, and accept, the organization and its practices (Aldrich & Fiol, 1994; DiMaggio & Powell, 1983; Meyer & Rowan, 1977; Meyer & Scott, 1983; Scott, 1995).

According to this theoretical perspective, institutional factors affect organizations' strategies and processes (Meyer & Rowan, 1977; Scott, 1995). Organizations that conform to the "rules of the game" (North, 1990) and become "isomorphic" with their environment (Meyer & Rowan) gain the legitimacy and resources needed to survive. Thus, an organization' s success depends more on its legitimacy than on efficient coordination and control of productive activities. In the lending context, institutional theory predicts that firms with stronger legitimacy should get better access to external financing.

Aldrich and Fiol (1994) distinguished cognitive legitimacy and sociopolitical legitimacy. Cognitive legitimacy refers to the extent the general public knows about the organization and its practices. When an activity becomes so familiar and well known that it is taken for granted, time and other organizing resources are conserved. The highest form of cognitive legitimacy is when an organization and its actions are so well known and accepted that it is taken for granted. Sociopolitical legitimacy refers to the extent to which a new organization conforms to recognized principles and accepted rules. It can be measured by how key stakeholders, the general public, and government officials accept the organization and its practices as "appropriate and right given existing norms and laws" (Aldrich & Fiol, p. 648).

This suggests that firms need to develop cognitive and sociopolitical legitimacy to get access to external financing. A firm that is well known to key stakeholders, that is viewed as following accepted rules and standards, and that has acceptable businesses and practices familiar to the potential fund providers should have better access to loans. Therefore, a key challenge for the firm is not only becoming "isomorphic" to the environment, but also making potential financial providers and related stakeholders aware and accepting of its practices.

Networks and External Financing

Here, we adopt the institutional view and argue that networks increase a firm's legitimacy, which in turn positively influences the firm's accessibility to external financing (Ahlstrom & Bruton, 2006). In the absence of effective market institutions, networks play an important role in spreading knowledge about a firm's existence and its practices. Networks also help a firm learn appropriate behavior and therefore obtain needed support from key stakeholders and the general public. In large part, networking substitutes for the lack of effective market institutions (Hoang & Antoncic, 2003; Peng, 2001; Redding, 1990), and can be an effective way for SMEs to access external financing, including bank loans in emerging economies.

Much of the entrepreneurship, finance, and economic literature on SME financing indicates that it is often difficult and expensive for SMEs to access bank financing, due in large part to information asymmetry between banks and firms (Ebben & Johnson, 2006; Winborg & Landstrom, 2000). Thus, it is both necessary and desirable for SMEs to find alternative sources of capital to satiate their need for capital. Various alternative sources of external debt financing may be available to SMEs, including trade credit, loans from relatives and friends, and support from governments. These alternative sources of financing appear to be critically important for SMEs in emerging economies, where more formal and extensive financial markets are typically underdeveloped (O'Connor, 2000; Smallbone & Welter, 2001), and where problems pertaining to information asymmetry and opportunism are often more pronounced (Boisot & Child, 1996). Further, these alternative sources of financing are often more accessible, convenient, and, sometimes, cheaper; government support programs provide loans with interest rates well below those offered by commercial banks. Networking, by helping SMEs access these sources, could reduce the need for bank loans. Several empirical studies support this point (Hussain, Millman, & Matlay, 2006; McMillan & Woodruff, 1999, 2002).

The above discussions suggest that networks provide contradictory forces to affect a firm's use of bank loans. On the one hand, a well-networked SME has legitimacy, information, and knowledge advantages, which promote the firm's access to bank loans. On the other hand, networks can reduce the need for bank loans by helping a firm access other sources of funding. But the net effect is likely to be different across different types of networks, which we discuss in the following sections.

The most common types of network ties are social ties, such as ties with friends and relatives (Coleman, 1988; Granovetter, 1985; Redding, 1990), and connections with managers of other firms (Birley, 1985; Larson, 1992; Uzzi, 1997). In the context of emerging economies, several authors have suggested that ties with government officials are critical for private firm survival (e.g., Peng & Luo, 2000; Xin & Pearce, 1996). To examine how different network ties influence external debt financing, particularly bank financing to private SMEs, we distinguish networks into three main types: (1) official networks--or networks with government officials; (2) managerial networks--we consider networks with top managers of supplier and of customer firms separately; and (3) social networks--similarly, we separate networks with relatives and friends from networks with members of social organizations and clubs. Figure 1 illustrates our theoretical model.

[FIGURE 1 OMITTED]

Official Networks and Bank Financing. SMEs in emerging economies are often presented with exciting, high-growth business opportunities, but must also confront a high degree of uncertainty in the business environment (Boisot & Child, 1996; Nguyen et al., 2006). In such countries, the market mechanism often coexists with (and is impacted by) a government-led redistributive mechanism, suggesting that government officials still have a strong influence on business practices (Boisot & Child; Li & Zhang, 2007; Nguyen et al., 2005). Managers' ties with government officials--the official networks--represent a special type of managerial resource in these countries (Chung, 2006; Li & Zhang; Nguyen et al.; Peng & Luo, 2000).

Compared with state-owned enterprises, privately owned SMEs receive little support from the government and typically lack market legitimacy (Li & Zhang, 2007; Nguyen et al., 2005; Xin & Pearce, 1996). Networking with government officials helps private firms to navigate through cumbersome procedures with state agencies, gain access to scarce resources, and enter closely regulated industries, and thereby improve their business performance (Chung, 2006; Peng, 2001; Peng & Luo, 2000; Tsang, 1994; Xin & Pearce). This is evidenced in various emerging economies (Peng), such as China (Li & Zhang; Peng & Luo; Xin & Pearce), Taiwan (Chung), and Eastern European countries (Smallbone & Welter, 2001). Vietnam is no exception in this regard (Le et al., 2006; Nguyen et al., 2006). Despite two decades of economic and business liberalization reforms, officials at all levels of government still have considerable power to approve specific business projects and allocate resources (Mallon, 2004; Meyer & Nguyen, 2005; Nguyen et al.). Furthermore, attitudes toward SMEs and the private sector vary greatly among local state officials who directly interact with private firms (Vietnam Competitiveness Initiative-Vietnam Chamber of Commerce and Industry [VNCI-VCCI], 2005). Under such conditions, close ties with government officials can mitigate the disadvantages of being a privately owned firm in Vietnam (Le et al.).

As an important element of the economy, the banking sector in Vietnam is still heavily regulated, despite considerable reform over the past two decades (O'Connor, 2000; World Bank, 2002). Government control over the banking sector is exercised in at least two ways. First, the four state-owned commercial banks (SOCBs) still dominate the banking sector. The four largest SOCBs accounted for about 70% of the total assets in the banking system by 2002 (World Bank) and 76% of total bank credit by 2003 (International Monetary Fund, 2003). The traditional close linkages between government officials and SOCBs suggest that official networks should benefit private firms in accessing loans from these banks. Second, barriers to entry are considerable, given that the State Bank of Vietnam controls quite tightly the granting of banking licenses, both for the establishment of new banks, as well as the provision of new banking services by established institutions (World Bank). Under such a situation, private banks may, themselves, rely on official networks, thereby granting government officials considerable influence over banking operations as a whole.

A recent study on bank lending in Vietnam showed that local banks face extreme uncertainty in lending to private SMEs, largely as a consequence of the lack of reliable information and effective law enforcement (Nguyen et al., 2006). In such situations, banks often consult relevant government officials for better information on, and/or endorsement for, those firms seeking a loan. This finding is consistent with other studies conducted in Vietnam (O'Connor, 2000; Tenev, Carlier, Chaudry, & Nguyen, 2003). If banks turn to government officials for information and advice on firms' creditworthiness, then networking with government officials should facilitate firms' access to bank loans. We therefore anticipate that networking with government officials improves a firm's accessibility to bank finance.

Conversely, one could argue that networking with government officials should help firms gain access to government support programs, thereby reducing the need for a commercial bank loan. As private SMEs play an important role in economic growth and job creation in emerging economies, governments of these countries often have support programs to promote the private sector (Smallbone & Welter, 2001; VNCI, 2006). Compared with commercial loans, these programs normally offer markedly lower interest rates and may have less stringent collateral requirements (VNCI). It is therefore understandable that private SMEs would prefer to utilize these sources of "soft financing" to "hard" commercial bank loans. In practice, however, government support programs are quite limited and normally restricted to targeted industries (George & Prabhu, 2000). In Vietnam, since the late 1990s, most government support programs of this kind have been channeled, as so-called "policy loans," through the state-run Social Policy Bank and Vietnam Development Bank. A recent study showed that this bank largely operates just like commercial banks, albeit with a more bureaucratic set of loan application procedures (VNCI). As a consequence, few private SMEs look for, or have access to, these "policy loans" provided by the government. It seems that such forms of government support, while desirable in theory, are, in practice, neither big enough nor accessible enough to drive Vietnamese SMEs away from commercial bank loans. Therefore, we hypothesize:

Hypothesis 1: The strength of a firm's official networks is positively related to the use of bank loans.

Managerial Networks and Bank Financing. The second type of network is those with managers of suppliers and customers. These networks help firms increase their legitimacy (and access to bank loans) in several ways. First, the networks help spread knowledge of the firm's existence and business practices to key stakeholders and the general public. This is especially important when firms apply for bank loans. To mitigate the lack of public data, bankers in emerging economies often have to rely extensively on informal information channels to learn about loan applicants (Nguyen et al., 2006; O'Connor, 2000). Consistent and positive information from different sources is critical in appraising loan applications from SMEs. The more a firm' s manager builds a network with managers of other firms, the higher the chance the firm will be familiar to banks. In short, this increases the firm's cognitive legitimacy (Aldrich & Fiol, 1994). Second, an endorsement and a reference from respected managers of supplier or buyer firms often helps create a positive image of the firm (Coleman, 1988; Granovetter, 1985; Nguyen et al.; Peng & Luo, 2000). Third, through networking, the firm owner learns appropriate business behavior from other managers, notably in terms of dealing with banks, thereby increasing the firm's sociopolitical legitimacy. And by increasing their legitimacy, this can positively influence a firm's ability to access a bank loan.

However, this theoretical proposition does not have particularly strong empirical support. While networking with managers of suppliers and customers can increase a firm's general legitimacy, it has not been shown to specifically improve a firm's access to bank loans (Petersen & Rajan, 1994). This could be because effective networking with managers also facilitates interfirm alliances (BarNir & Smith, 2002), and benefits a firm in accessing trade credit (McMillan & Woodruff, 1999, 2002). This is especially true for emerging economies such as in Vietnam, where private SMEs must operate without a developed legal framework and financial market. In such an environment, trade credit with business partners is often pursued by firms (McMillan & Woodruff, 1999, 2002). In their study of informal credit in Vietnam, McMillan and Woodruff (1999) found trade credit quite common among surveyed firms, with 57% of ongoing customer relationships and 53 % of ongoing supplier relationships involving some element of trade credit. Conversely, only 22% of firms surveyed had bank loans.

However, the benefits of trade credit can conceivably work in opposite directions, depending on whether the focal firms are suppliers or customers. Thus, combining networking for both suppliers and customers might obscure the true effect of these networks on bank lending, thereby resulting in a distorted result. To address this issue, we separate networks with suppliers from those of networks with customers, and examine the relative impact of both these networks on bank financing.

As customers, private firms may benefit from trade credit granted by their suppliers. Even in developed countries, the major source of capital for SMEs is trade credit from suppliers (McMillan & Woodruff, 2002). Firms' legitimacy and reputation influence the suppliers' perception of payment default and willingness to grant trade credit (Ebben & Johnson, 2006). Firms get more trade credit from their suppliers when they have long-term business relationships (or are "locked in") with suppliers, have frequent interactions with suppliers, or are in the same networks with suppliers (McMillan & Woodruff, 1999). In this case, strong ties with suppliers should help convince suppliers to grant trade credit to a firm, thereby reducing the use of bank loans.

The same argument would suggest the opposite impact stemming from networking with customers. Specifically, customers with strong ties to a firm should seek more trade credit from that firm, for at least three reasons. First, these customers have demonstrated their trustworthiness to the firm, resulting in a perception of low risk of payment default (Nguyen et al., 2005). Second, these customers tend to be long-term customers (McMillan & Woodruff, 2002). Given that the most challenging task for Vietnamese private firms is to find customers (Mekong Project Development Facility [MPDF], 2002), retaining such long-term customers can be critical for business success, even if it means granting more trade credit to them. Finally, those firms that are able to show a strong client base through their customer networks should be able to convey significant confidence from banks (Nguyen et al., 2006). Thus, a strong network with customers should increase both the need for, and accessibility to, bank loans. Therefore, we hypothesize:

Hypothesis 2a: The strength of a firm's networks with suppliers is negatively related to the use of bank loans.

Hypothesis 2b: The strength of a firm's networks with customers is positively related to the use of bank loans.

Social Networks and Bank Financing. Social network ties in this study include ties with friends and family, and with members of social associations and clubs, but who do not belong to official or managerial networks. Social networks have been found to be important for SMEs' success in many contexts (Birley, 1985; Hoang & Antoncic, 2003; Larson, 1992; Redding, 1990; Singh, Hills, Hybels, & Lumpkin, 1999). Social networks can be viewed as the platform through which managers gain access to a variety of resources from others, including access to capital, information and advice, emotional support, and endorsement (Coleman, 1988; Granovetter, 1985; Hoang & Antoncic). Small firms become dependent upon their managers' personal networks as a supplement to their own business resources. This is particularly relevant when we consider Vietnam's culture, which tends to emphasize collectivism rather than individualism (Ralston, Nguyen, & Napier, 1999). Individuals are evaluated not only based on their own competency and contribution, but also to whom they are connected. Similar to China, ties based on family, relatives, school and university peers, or hometown connections are all important in Vietnamese society (Truong, Phan, & Nguyen, 1997). Thus, while organizational ecologists imply that organization and industry characteristics are the primary source of private firms' legitimacy (Hannan & Freeman, 1984), we argue that in Vietnam, individual social ties also influence a firm's degree of legitimacy.

Similar to official and managerial networks, social networks help firms spread knowledge about their existence, and can also be a signal of reputation (Coleman, 1988; Granovetter, 1985). In this regard, a firm's social networks can facilitate its access to bank financing. In their study on bank financing to SMEs in Vietnam, Nguyen et al. (2006) found that bankers sometimes turn to their own social networks for information and advice on the creditworthiness of a potential firm applicant. Therefore, if a firm's owner or manager and a banker have a common friend or relative, or belong to the same social network, it can accelerate the bank's decision-making process.

However, social networks also help SMEs gain access to informal sources of finance, such as from relatives and friends. Studies have shown that small firms often must rely on informal sources of finance, before going to commercial banks (Carlier & Tran, 2004; Ebben & Johnson, 2006; Winborg & Landstrom, 2000). This is especially true in the context of emerging economies (Hussain et al., 2006; Peng, 2001; Smallbone & Welter, 2001). Hussain et al. compared Chinese and British SMEs in their use of external sources of finance, though various stages of development. They found that at the initial stage, both British and Chinese SME owners relied exclusively on financial support from their immediate family. After 5 years of operations, however, the British SME owners relied more on formal financial institutions, while the Chinese SME owners were still relying considerably on funds from immediate family. In Vietnam, a recent survey estimated that only about 55% of private firms had access to formal bank credit of one kind or another (Steer & Taussig, 2002). Similar to Chinese SMEs, the principal sources of financing of many private SMEs in Vietnam are often informal (i.e., from friends and relatives, and other third parties), a direct result of social networks (Nguyen et al., 2006). In this regard, the social networks actually reduce the need to access formal bank lending.

Note that we have combined the networks with relatives and friends with the network for social organizations and associations in our discussion thus far. Compared with the well-known role of networks with relatives and friends (e.g., Hussain et al., 2006; Redding, 1990), the networks with members of social organizations and associations have attracted relatively less attention in the literature. While financial support from relatives and friends is popular, we argue that this "love money" is limited, and mostly fits with firms in the trading and service sectors, and/or with those SMEs at an early stage of development (Wong & Ho, 2007). For growing manufacturing firms, they need to look for larger sources of finance than can usually be provided by individual friends and family. Several studies conducted in emerging economies suggest that networking with members of social organizations helps small private firms have better access to venture capital (Ahlstrom & Bruton, 2006) and business angels (Wong & Ho). Another factor, which may be more specific to Vietnam, is that commercial banks have very strict collateral requirements. Some firms reported that because they lacked the right kind of collateral to enable them to borrow from banks, they had to go through a third party to get the loans from banks, and pay a "fee" to the intermediary for that service (Carlier & Tran, 2004). Such a loan, while originating from a bank, would be reported as coming from a third party. Networking with social organizations and associations facilitates the identification of trusted "third parties" that would be willing to borrow on behalf of the firm. This suggests that networks with members of social organizations also reduce the need for bank loans, albeit rather deceptively in some cases. Therefore, we hypothesize:

Hypothesis 3a: The strength of a firm's networks with relatives and friends is negatively related to the use of bank loans.

Hypothesis 3b: The strength of a firm's networks with members of social clubs and organizations is negatively related to the use of bank loans.

Methods

Vietnam as the Research Site

We chose Vietnam as the empirical setting for this study on the relative impact of different networks on firms' accessibility to bank finance. Vietnam is particularly suitable because the country has gone through a major economic transition process and yet, weaknesses in its formal institutions remain major obstacles for firms (Meyer & Nguyen, 2005; Nguyen et al., 2006). SMEs, while burgeoning in aggregate number, mostly remain small, informal, and short-term oriented. From the perspective of Vietnamese banks, SMEs are seen as a new, potentially lucrative, but very risky segment of the commercial loan market (Nguyen et al.).

In this context, networking has been used extensively by both bankers and SME managers in conducting business (Nguyen et al., 2006; O'Connor, 2000). Managers use different types of networks for different business purposes (Nguyen et al., 2005), including access to external finance (Nguyen et al.). This allows us to distinguish between different types of networks that may be facilitating firms' access to bank loans.

Sample and Procedure

Our sampled population was privately owned manufacturing sector SMEs located in Vietnam. A stratified sampling strategy was adopted to collect data. Two main criteria to select firms for the survey were applied: geographical area and year of establishment. Geographically, the distribution of the sampled SMEs mirrored that of the country's corporate community. There are three distinct regions of the country, although the language and culture between the three are largely the same. Most firms examined here were located in the south, followed by the north and central regions. Examining the characteristics of the firms, no significant differences were found among the three. To ensure that the surveyed sample provided a representative picture of Vietnam's private sector, areas at different levels of development were included. Hence, geographically, they range from the economic powerhouses of Ho Chi Minh City, Hanoi, Hai Duong, and Binh Duong to provinces that have displayed slower economic development, such as Ha Tay, Nam Dinh, Thanh Hoa, and Nghe An. Firms were also selected based on the year of establishment. A number of firms established before and after 2000 were determined for the survey. The year 2000 was chosen as the referent date because a new enterprise law, effective in January 2000, considerably eased the firm registration process. As a result, the number of newly established firms sharply increased after 2000 (Nguyen et al., 2006).

We retained local researchers who were native to the main cities and provinces where the survey was conducted (i.e., Hanoi, Thanh Hoa, Nghe An, and Ho Chi Minh City), and were trained in both data collection methods and the reasoning behind each item in the questionnaire. These researchers obtained lists of registered private manufacturing firms from the Tax Bureau and economic planning departments of targeted provinces and municipalities. Based on the two criteria referred to above (year of establishment and location), 400 private manufacturing SMEs were selected for the survey. The local researchers then directly contacted these firms, delivered the survey instrument, followed up, and collected the completed questionnaires.

The survey was conducted over 4 months from April to July 2005. Of 400 questionnaires sent, 230 were returned, giving an average response rate of 57.5%. Two hundred and fourteen collected questionnaires were usable for the research. We compared key characteristics (i.e., firm age, size, location) of firms in our sample with the wider corporate population and found nonsignificant differences. The sample satisfactorily represents the wider population.

Variables and Measurement

We initiated this research with a series of semi-structured, in-depth interviews with 15 bank officers and seven private SME owners, using a series of open-ended questions. We then developed a draft questionnaire, based on the current literature and some of the findings from the in-depth interviews. The first draft of the questionnaire was distributed to six people in the academic and business community, to check its face validity. The questionnaire was then adjusted and sent to owners and managers of 43 private manufacturing SMEs, to test its face validity and readability. The final version of the questionnaire was further adjusted, based on the results of this pretest. The full set of variables in the final version was as follows.

Dependent Variables. Following Blackwell and Winter (1997), we used the ratio of bank loans to total capital, in 2004, as a proxy for the firm' s use of bank loans (i.e., bank loan to total capital ratio).

Independent Variables. Key independent variables were: (1) official networks, (2) managerial networks (with suppliers and with customers), and (3) social networks (with relatives and friends, and with members of social organizations and clubs). For official networks, owners and managers were asked the extent to which they utilize relationships with government officials, at all levels, for business purposes. Three items measuring this construct had a Cronbach's alpha of .76. For managerial networks, we considered networks with suppliers and networks with customers separately. Owners and managers were asked the extent to which they had utilized networks with the top managers of suppliers and customers, respectively. These items of official and managerial networks were adapted from Peng and Luo (2000). Similarly, for social networks, we separated networks with relatives and friends from networks with members of social organizations and clubs. Owners and managers were asked the extent to which they bad utilized networks with relatives and friends, and with members of social organizations and clubs for business purposes. All items were in a 5-point scale format.

Control Variables. Based on previous studies (Berger & Udell, 1995; Coleman, 2000; Van Auken, 2001), and results from the interviews, we controlled for firm age, firm size (measured by registered capital), legal forms of ownership (i.e., joint stock companies, limited liability companies, partnership companies, and private companies), owner's experience, owner's education, bank ownership (i.e., whether state owned or private banks), and the number of banking services the firm used.

Results

Descriptive Statistics

Thirty percent of our respondents (65 firms) reported that they did not borrow from banks (they had a bank loan/capital ratio of 0). Almost all of these firms had not even applied to a bank, suggesting that they had no need of bank financing. Therefore, we separated the respondents into two groups: (1) those who had not borrowed from banks; and (2) those who had borrowed from banks. We then created two subdependent variables for the use of bank loans. The first one (for the whole sample)--probability of having a bank loan--is a binary variable (yes/no) on having a bank loan. The second one (only for those firms with bank loans)--a bank loan ratio--is a continuous variable, with reported positive ratios of bank loan/total capital.

Table 1 presents the descriptive statistics and correlations for the key variables. Official networks significantly correlate with all other types of network, and the use of a bank loan at p < .05. The average firm in our sample had been in business for 7 years, had 70 employees, and a registered capital of VND 1,914,000 (equivalent to about US$120,000).

Hypotheses Testing

We first checked and corrected for violations of the normality assumption and multicollinearity problem by using correlation matrix and the variance inflation factor. The results indicated an inconsequent collinearity among variables. These independent variables were acceptable for running regressions (Hair, Anderson, Tatham, & Black, 1998).

Two steps were taken in testing the hypotheses. In step 1, we tested if our variables of interest influenced the firm's probability of having a bank loan, using logistic regression. Table 2 summarizes the logistic regression results.

That model was statistically significant, with [chi square] = 55.89 (p < .01), indicating that the variables as a set reliably distinguished firms that had a bank loan from those that had not. The Wald criterion showed that firm age and the number of banking services were positively related to the probability of having a bank loan. In other words, firms that have a longer history and use more banking services are more likely to have taken out bank loans. Official networks were positively related to having a bank loan (p < .001), thus providing support for hypothesis 1. Neither networks with suppliers nor with customers were significant in this logistic regression. Therefore, hypothesis 2a,b was not supported. Networks with friends and relatives were also negatively related to having a bank loan, but were significant only at p < .1 level. Therefore, hypothesis 3a was not supported. Networks with members of social organizations were significantly and negatively related to having a bank loan (p < .001), supporting hypothesis 3b.

In step 2, only firms that had borrowed from banks were selected. We then examined if the variables of interest influenced the bank loan ratio, using hierarchical regression. First, control variables (owner's education, owner's experience, firm ownership form, firm age, firm size, bank ownership, and number of bank services) were included in the equation (control model). Second, independent variables (official network, network with customer, network with supplier, network with members of social organizations and clubs, and network with friends and relatives) were entered (main model). Table 3 summarizes the regression results.

The control model was significant (adjusted [R.sup.2] = .122, F = 3.146, p< .01). Two control variables were significant, namely, owner experience ([beta] = -.286, p < .01) and number of bank services ([beta] = .326, p < .01). The model remained significant when variables of interest (official networks, networks with customers, networks with suppliers, networks with members of social organizations and clubs, and networks with friends and relatives) were entered in the main model (adjusted [R.sup.2] = .257, F model = 4.119, p < .001, F change = 4.68, p < .01). Official networks were not significantly related to the use of bank loan. Therefore, hypothesis 1 was not supported in this regression. Networks with suppliers were significantly and negatively related to the use of bank loans ([beta] = -.477, p < .001), supporting hypothesis 2a. Networks with customers, on the other hand, were negatively related to the use of bank loans, but significant only at p <. 1 ([beta] = .191, p < .1). Hypothesis 2b was therefore not supported. Both types of social networks were not significantly related to the use of bank loans. Therefore, hypothesis 3a,b was also not supported in this regression.

Table 4 summarizes the results from both steps.

Discussion

The central argument of this article is that in the absence of effective market institutions and reliable business information, banks rely largely on their evaluation of firm legitimacy to make loan decisions. Networking, by helping SMEs improve their legitimacy, is believed to improve their accessibility to bank loans. That notwithstanding, networking also helps SMEs access other sources of external debt financing, thereby potentially reducing the need for bank loans. Without accounting for these contradictory effects of networking, we may overstate the impact of different networks on bank financing for SMEs, particularly in emerging economies like that of Vietnam. This study examines the relative effects of different networks on private firm bank financing. Different types of networks (official networks, networks with customers, networks with suppliers, networks with members of social organizations, and networks with friends and relatives) are empirically tested, using data collected from a sample of Vietnamese private manufacturing finns.

Our two analysis steps are parallel to two stages of getting a bank loan. The logistic regression helps identify significant factors for getting bank loans. The ordinary least square regression, on the other hand, identifies factors that have significant associations with the ratio of bank loans after the firm already had access to bank loans. None of the network variables were significant in both regressions. Three types of networks (official networks, networks with suppliers, and networks with social organizations) were significant in one of the two regressions. The other two types of networks (networks with customers and networks with relatives and friends) were significant in either one of the two regressions, but only at p < .10 level. Taken together, each network type showed some association with bank financing, but at different stages of getting bank loans, and with different magnitudes. These results generally support our central hypothesis that different networks play different roles, and that not all networks are equally important in helping an SME to access bank loans.

Firm Networks and Bank Financing

We hypothesized that official networks have a positive association with the use of bank loans. Our results showed that networks with government officials are significantly and positively associated with the possibility of acquiring bank loans, but not so with the bank loan ratio. In other words, the strength of the official networks helps distinguish firms that had bank loans from those that did not. Among just those firms that did borrow from banks, however, the strength of official networks does not appear to influence the actual amount of bank lending. This finding might suggest that official networks are important for firms seeking to borrow from a bank for the first time, but are of less pertinence for those SMEs that already have access to bank loans. Conversely, managerial networks (i.e., networks with suppliers and customers) did not significantly relate to the probability of having a bank loan, but did significantly relate to the bank loan ratio. As we predicted, the bank loan ratio is negatively related to the strength of networks with suppliers, and positively related to the strength of networks with customers.

Our logistic regression results show that social networks, especially networks with members of social organizations and clubs, significantly distinguish firms that had bank loans from those that did not. Firms with stronger social networks were less likely to borrow from banks than others. In our sample, almost all the firms that did not borrow from banks had never even applied for a bank loan. Thus, the result supports our argument that social networks reduce the need for bank loans. Note that the networks with members of social organizations, while not attracting as much discussion as networks with relatives and friends, were strongly significant in our study. As Vietnamese private manufacturing firms passed their founding stage, funding from family and friends may become too limited. When accessing bank loans is troublesome, many SMEs have to turn to other sources such as venture capital, business angels, or informal loans. And in this context, networks with members of social organizations serve as a vehicle for the identification of such alternative sources.

Among the control variables, owner experience was negatively and significantly related to the use of bank loans. From the bank's perspective, owner experience should induce a positive assessment of the firm's creditworthiness. However, owner experience in the current Vietnamese context may be negatively related to the need or willingness to borrow from banks. First, firms that were founded before the year 2000 had to go through a strict registration process, which required evidence of strong financial capability. These firms, associated with more experienced owners in our sample, may have lower needs to borrow from banks. Second, with new progress in the Vietnamese reform, more firms are being founded by "professional entrepreneurs," consistent with observations in other emerging economies (Peng, 2001). These professional entrepreneurs are generally younger and less experienced in business than the average entrepreneur in Vietnam. However, they are more growth oriented and long-term oriented, and more confident in approaching banks for loans. These contextual and personal factors become "imprinted" in the firm's business practices (Hannan, Burton, & Baron, 1996), and explain why, in Vietnam, less experienced entrepreneurs use more bank loans than experienced entrepreneurs.

Also in our model, the number of services a firm buys from a bank is strongly related to both the probability of the firm having a bank loan and the ratio of bank loans in the firm's capital structure. This number of banking services reflects the strength of business relationships between the firm and the bank. Studies on banking relationships have shown that close relationships with banks help firms better understand and conform to the "rules of the game," become more isomorphic with the lending context, and enhance firm legitimacy (e.g., Meyer & Rowan, 1977; Petersen & Rajan, 1994). On the other hand, these close relationships help banks understand better the firms, improving cognitive legitimacy of the firms. These relationships are even more important for firms in emerging economies where market institutions are underdeveloped and business data are generally unavailable (Nguyen et al., 2006). The significance of this variable suggests that direct business relationships with the banks are effective mechanisms for improving the firm's legitimacy and creditworthiness, in addition to networking with other parties.

Theoretical Implications

This study makes several important contributions to the existing literature. First, while the importance and challenges of getting bank loans for private SMEs is already well established in the literature, most previous studies have focused on SMEs in more developed market economies. Compared with their counterparts in developed economies, private SMEs in emerging economies typically face even greater challenges in getting bank loans, largely because the legal and institutional framework and business information systems are not so well developed. Our study contributes to this line of research by demonstrating that under the absence of effective institutions and business information, the institutional perspective appears to be very relevant in explaining a firm's accessibility to bank lending. However, a richer theoretical foundation that combines different perspectives would benefit future research in emerging economies. For example, from a resource-based view of the firm, an SME's networks in an emerging economy can be seen as a critical resource (Peng, 2001). However, the relative importance of these resources might change over time, as a country's economic and business policy reforms progress (Peng, 2003). It would be interesting to combine the resource-based view of the firm and the institutional perspective, so as to examine the role of this resource on bank financing across different levels or stages of institutional development.

Second, previous studies on networking and bank financing have focused mainly on direct ties between banks and firms. This study, to our knowledge, is the first one that examines the relative impacts of different networks on SMEs' accessibility to bank loans. While there is a general consensus in the literature that networking is critical for SMEs in emerging economies, the complex impacts of different networks on firm businesses have not been adequately studied. We have demonstrated that different networks serve different purposes, and firms would be well advised to align their networking efforts with specific purposes. Future research could further explore this idea in other functions of business (e.g., access to markets and other key resource inputs, such as access to land).

Finally, our article views an individual's own network ties as an important source of a firm's legitimacy. While the important role of individual managers' network ties on general firm performance in emerging economies has been well established (Li & Zhang, 2007; Peng & Luo, 2000; Xin & Pearce, 1996), this specific role of individual managers as legitimacy-building agents has not been explicitly discussed. This complements the traditional ecological perspective that views organization and industry characteristics as the primary source of firm legitimacy (Hannan & Freeman, 1984). In an uncertain business environment, where reliable data on firms and industries is not available, managers' network ties can influence the public perception, and thus the legitimacy, of a company.

Similarly, our study contributes to the literature of social networks and entrepreneurship. Most studies on entrepreneurs' networks have tended to focus on entrepreneurs as information-brokering agents (Birley, 1985; Burt, 1992; Butler, Brown, & Wai, 2003; Hoang & Antoncic, 2003; Larson, 1992; Singh et al., 1999). In these studies, entrepreneurs who are more connected, who penetrate into central positions of networks, can play a brokering role for others. These information-brokering entrepreneurs, it is argued, are more likely to recognize opportunities. Our study suggests another way social networks could be beneficial for entrepreneurs and SMEs: to effectively build legitimacy. Firms with stronger legitimacy are in a better position to mobilize resources for realizing such opportunities (Meyer & Rowan, 1977; Nguyen et al., 2005). This legitimacy-building role is especially important for entrepreneurs in emerging economies, where institutions and factor markets tend to be underdeveloped. Future research could distinguish entrepreneurs' networking strategies that focus on information brokering from those that focus on legitimacy building.

Managerial Implications

The most important implication from this study, for owners and managers of SMEs, is that different networks serve different purposes, and thus, they should seek to align their networking efforts with specific business purposes, at different stages of development. For example, social networks may help firms avoid the need for bank loans, by providing access to informal sources of funding, while networking with government officials is important for SMEs that are attempting to borrow from banks for the first time. Managerial networks, on the other hand, seemingly have a dichotomous effect on bank financing, thus: A strong network with suppliers reduces the need for bank loans, while a strong network with customers promotes the need for bank loans.

Among the control factors, the number of bank services used by firms has a strong relationship with bank financing. One simple piece of advice to small business owners is to select a single bank and seek to use several services from that bank. Conversely, shopping around, trying to look for the cheapest bank for each specific banking service is not advisable, because this may adversely impact the firm-bank relationship.

The relative importance of various factors influencing bank financing has particular relevance for SMEs in Vietnam and other emerging economies. In these countries, the future development of the economy is greatly dependent on the success of the burgeoning private sector. In the absence of effective market institutions that provide reliable business data and secure contracts, both banks and private firms are forced to rely extensively on various networks for their activities. In time, a country's institutions may well develop, allowing banks to use more standard data and lending procedures, such as those commonly seen in developed countries. Until then, however, private firms in many emerging economies--including Vietnam--will need to cultivate various network ties and demonstrate their creditworthiness.

The authors acknowledge the guest editors of the Entrepreneurship Theory and Practice special issue--Professors David Ahlstrom, Garry Bruton, and Krzysztof Obloj--and the participants of the Texas Christian University-Chinese University of Hong Kong Entrepreneurship Theory and Practice Conference, Fort Worth, TX (March 28-30, 2007). Our thanks also to an anonymous reviewer for helpful comments on an earlier draft of this article. The article was written when Thang Nguyen was a visiting professor at the University of Macau. The authors contributed equally and are listed alphabetically.

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Thang V. Nguyen is a PhD candidate and lecturer in NEU Business School, Hanoi, Vietnam.

Please send correspondence to: Ngoc T.B. Le, tel.: (84-4) 869-0055 (ext. 132); e-mail: lbngoc@bsneu.edu.vn, and to Thang V. Nguyen at nvthang@bsneu.edu.vn.
Table 1
Correlation Matrix

                                           Mean       SD         1

 1 Education                                1.56        .934
 2 Experience                              12.25       7.24   -.02
 3 Firm ownership                           3.04        .780   .28 **
 4 Firm age                                 7.2        5.1     -.02
 5 Firm size (log for correlation)      1,914.5    2,260.2     -.22 *
 6 Bank ownership                           1.25        .433   -.04
 7 Number of services                       3.97       1.269   -.13
 8 Official network                         3.10        .850    .08
 9 Network with customers                   4.23        .621    .08
10 Network with suppliers                   4.05        .732   -.05
11 Network with members of social
   organizations                            2.57       1.04    -.15 *
12 Network with relatives and friends       3.64        .947    .13
13 Probability of having a bank loan         .710       .455    .07
14 The use of bank loan                    22.89      21.344    .09

                                           2         3         4

 1 Education
 2 Experience
 3 Firm ownership                       -.05
 4 Firm age                              .34 **   -.04
 5 Firm size (log for correlation)       .05      -.34 **    .04
 6 Bank ownership                       -.14 *     .02      -.14
 7 Number of services                    .04      -.18 **    .12
 8 Official network                      .10      -.05       .11
 9 Network with customers               -.05       .15 *     .01
10 Network with suppliers                .04      -.02      -.02
11 Network with members of social
   organizations                         .05      -.15 *     .15 *
12 Network with relatives and friends   -.03       .19 **    .00
13 Probability of having a bank loan    -.10      -.13       .12
14 The use of bank loan                 -.06      -.10       .12

                                           5         6         7

 1 Education
 2 Experience
 3 Firm ownership
 4 Firm age
 5 Firm size (log for correlation)
 6 Bank ownership                        .08
 7 Number of services                    .40 **    .05
 8 Official network                      .04      -.10       .11
 9 Network with customers                .05       .00       .03
10 Network with suppliers                .10       .07       .09
11 Network with members of social
   organizations                         .07       .03       .09
12 Network with relatives and friends   -.11      -.03      -.01
13 Probability of having a bank loan     .07      -.01       .31 **
14 The use of bank loan                  .05       .04       .33 **

                                           8         9        10

 1 Education
 2 Experience
 3 Firm ownership
 4 Firm age
 5 Firm size (log for correlation)
 6 Bank ownership
 7 Number of services
 8 Official network
 9 Network with customers                .21 **
10 Network with suppliers                .25       .50 **
11 Network with members of social
   organizations                         .35 *     .04       .15 *
12 Network with relatives and friends    .24 **    .05       .04
13 Probability of having a bank loan     .20 **   -.01      -.12
14 The use of bank loan                  .24 **    .02       .02

                                          11        12        13

 1 Education
 2 Experience
 3 Firm ownership
 4 Firm age
 5 Firm size (log for correlation)
 6 Bank ownership
 7 Number of services
 8 Official network
 9 Network with customers
10 Network with suppliers
11 Network with members of social
   organizations
12 Network with relatives and friends    .20 **
13 Probability of having a bank loan    -.01       .02
14 The use of bank loan                 -.02      -.03      .72 **

* Correlation is significant at the .05 level (two-tailed).

** Correlation is significant at the .01 level (two-tailed).

SD, standard deviation.

Table 2
Logistic Regression on Probability of
Getting a Bank Loan

                                          B          SE     Wald

Owner education                         .076        .240     .101
Owner experience                       -.060        .031    3.715 *
Firm ownership                         -.010        .319     .001
Firm age                                .138        .059   -5.442 **
Firm size                              -.288        .440     .427
Bank ownership                          .674        .471    2.045
Number of services                      .916        .209   19.24 ****
Official network                       1.120        .306   13.36 ****
Network with supplier                   .105        .324     .105
Network with customer                  -.479        .384    1.552
Network with relatives and friends     -.403        .239    2.828 *
Network with members of social         -.510        .221    5.342 **
  organizations and clubs
Constant                              -1.967       2.224     .783
-2 log likelihood                    161.795
Cox and Snell R square                  .279
Nagelkerke R square                     .387
Chi-square                            55.89 ****
Percentage of correct prediction      77.8

* p < .1; ** p <.05; *** p < .01; **** p < .001.
SE, standard error.

Table 3
Summary of Ordinary Least Square

Regression Results                     Control model   Main model

Owner education                           .139           .081
Owner experience                         -.286 ***      -.256 ***
Firm ownership                            .100           .059
Firm age                                  .088           .058
Firm size                                -.068          -.094
Bank ownership                           -.094          -.045
Number of services                        .326 ***       .397 ****
Official network                                         .074
Network with supplier                                   -.477 ****
Network with customer                                    .191
Network with relatives and friends                       .082
Network with members of social                           .088
  organizations and clubs
F model                                  3.146 ***      4.119 ****
Adjusted [R.sup.2]                        .122           .257
[R.sup.2] change                                         .161
F change                                                4.68 ***

* p < .1; ** p < .05; *** p < .01; **** p < .001.

Table 4
Summary of the Results

                                          Probability
                           Hypothesized    of having       The use of
Variables                  relationship    bank loan       bank loan

Significant control
    variables
  Firm age                               Significant     Nonsignificant
  Owner experience                       Nonsignificant  Significant
  Number of banking
    services                             Significant     Significant
Hypotheses
  Hypothesis 1: official   Positive      Supported       Not supported
    networks
  Hypothesis 2a: networks  Negative      Not supported   Supported
    with suppliers
  Hypothesis 2b: networks  Positive      Not supported   Not supported
    with customers                                         (significant
                                                           at p < .10)
  Hypothesis 3a: network   Negative      Not supported   Not supported
    with friends and                       (significant
    relatives                              at p < .10)
  Hypothesis 3b: networks  Negative      Supported       Not supported
    with social
    organizations
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