Bureaucratic Systems’ Facilitating and Hindering Influence on Social Capital
1042-2587
© 2013 Baylor University
E T&P
Bureaucratic Systems’
Facilitating and
Hindering Influence
on Social Capital
Patrick A. Saparito
Joseph E. Coombs
This study demonstrates how banks’ bureaucratic systems (i.e., formalization, management
continuity, customer orientation) are associated with social capital’s relational and cognitive
dimensions. We collected survey data from a matched sample of 884 small- and mediumsized enterprises (SME) executives and 217 bank managers across 22 banks to test hypothesized relationships. Our results showed that formalization is negatively associated with
both dimensions of social capital, while management continuity and customer orientation
are positively associated with them. These results are a first step in answering calls in the
literature to study bureaucratic systems’ influence on social capital. Theoretical and future
research implications are discussed.
Introduction
Social capital plays an important role in investor–small- and medium-sized enterprise
(SME) relationships (Le & Nguyen, 2009; Sapienza & Korsgaard, 1996; Shane & Cable,
2002; Uzzi & Lancaster, 2003; Yli-Renko, Autio, & Sapienza, 2001). Social capital helps
increase investors’ information and understanding of SMEs (Yli-Renko et al.) resulting in
greater access to both equity and debt funding alike (Le & Nguyen; Shane & Cable; Uzzi
& Lancaster). While this important research examines social capital as an antecedent to
resource acquisition (i.e., knowledge, financial capital), little attention has been paid to the
antecedents of social capital within SME–investor relationships. Indeed, Payne, Moore,
Griffis, and Autry (2011) point out that over 90% of social capital research treats social
capital as an independent variable.
In practice, many banks struggle with configuring their bureaucratic systems
in attempts to enhance their client relationships with SMEs (Berger & Udell, 1998).
Researchers acknowledge the importance of bureaucratic systems’ influence on social
relationships (e.g., Adler & Kwon, 2002; Nahapiet & Ghoshal, 1998; Payne et al., 2011),
and indeed suggest this influence is “inevitable under conditions of repeated action”
Please send correspondence to: Patrick A. Saparito, tel.: 610-660-1157; e-mail: psaparit@sju.edu, and to
Joseph E. Coombs at jecoombs2@vcu.edu.
May, 2013
DOI: 10.1111/etap.12028
625
(Adler & Kwon, p. 19). Adler and Borys (1996) argue that whether the influence is
negative or positive is based upon whether or not bureaucratic systems depersonalize
interaction and attenuate employees’ abilities to develop unique understandings about the
task at hand. However, despite repeated calls for research that studies bureaucratic
systems’ influence on social relationships (e.g., Adler & Borys; Adler & Kwon; Nahapiet
& Ghoshal), little work has focused upon this relationship.
We respond directly to these calls and attempt to make a focused contribution to the
literature. In particular, our purpose is to examine how bank-level bureaucratic systems
influence social capital within bank–SME relationships. By doing so, our study takes the
rare steps of a multilevel approach and an examination of social capital as a dependent
variable (Payne et al., 2011). We test our hypotheses on a matched sample of 884 SME
executives and 217 managers across 22 banks. Data from bank managers measure the
bank-level bureaucratic systems (i.e., formalization, management continuity, and customer orientation), while data collected from SME executives measure social capital’s
relational (i.e., trust) and cognitive (i.e., shared values) dimensions. We conclude by
discussing our results and implications for future research.
Social Capital Dimensions
Adler and Kwon (2002, p. 23) define social capital as “the goodwill available to
individuals or groups.” The general intuition behind the concept of social capital is that
trust, expectations of reciprocity, and shared values and norms facilitate resource flows
and promote group action (Adler & Kwon; Nahapiet & Ghoshal, 1998). Social capital can
provide differential access to various resources and thereby be used for an individual’s
benefit and competitive advantage (Burt, 1992; Portes, 1998). For SMEs, social capital
can provide access to critical resources necessary for firm survival and growth (Morse,
Fowler, & Lawrence, 2007; Packalen, 2007).
The social capital literature has two primary research streams. The first locates social
capital’s source in the structure of a network’s social ties (Le & Nguyen, 2009; Zhang,
Souitaris, Soh, & Wong, 2008). For example, Coleman (1990) suggests that dense ties
within a collectivity foster self-enforcing norms facilitating the attainment of group goals.
The second research stream focuses on the content of specific ties (Adler & Kwon, 2002).
For instance, Uzzi (1999) found that trust-filled ties with banks facilitated an SME’s
access to credit, while Yli-Renko et al. (2001) reported that firm-trusting ties with venture
capitalists were associated with greater knowledge transfer. Consistent with research
examining investor–SME relationships (e.g., Uzzi; Uzzi & Lancaster, 2003; Yli-Renko
et al.), we focus on the content of specific ties.
Social capital is increasingly viewed as a multidimensional construct (Nahapiet &
Ghoshal, 1998; Tsai & Ghoshal, 1998). Nahapiet and Ghoshal identify three dimensions
of social capital: structural, relational, and cognitive. The structural dimension refers to
the pattern of network relationships. Network structure includes the existence or absence
of connections between a focal party and other actors (bridging approach) and the overall
pattern of relationships within a group (bonding approach). Thus, the structural dimension
reflects “the impersonal configuration of linkages between people and units” (Nahapiet &
Ghoshal, p. 244).
While the structural dimension focuses on the network structure of social relationships, Nahapiet and Ghoshal’s (1998) relational and cognitive dimensions focus on the
content of ties with specific actors. More specifically, the relational dimension refers to
the personal relationship between specific parties that develops over time (Granovetter,
626
ENTREPRENEURSHIP THEORY and PRACTICE
1985; Nahapiet & Ghoshal). Trust appears as the key attribute of the relational dimension
(Nahapiet & Ghoshal). In discussing the relational dimension, Nahapiet and Ghoshal’s
conceptualization of trust is based upon the notions of reciprocity and expected goodwill
that build strong interpersonal bonds. Trust enables sequential business interaction where
one party must act first with the expectation that the other party will fully respond and
uphold their commitments at a later time. Thus, trust acts as a social mechanism allowing
parties to take actions with confidence that future obligations will be fulfilled and vulnerabilities will not be exploited (Ouchi, 1980; Uzzi, 1999).
Finally, the cognitive dimension of social capital refers to shared values, interpretations, and systems of meaning among parties that provide a basis for making sense of
knowledge and classifying it into perceptual categories (Nahapiet & Ghoshal, 1998; Tsai
& Ghoshal, 1998). Shared values, interpretations, and systems of meaning facilitate
learning and knowledge transfer allowing individuals to share each other’s thinking
processes. These common understandings help individuals make sense of and interpret the
world around them (Nonaka, 1994). Consistent with research examining investor–SME
relationships, our focus is on the content of specific ties between parties. Consequently,
we focus on social capital’s relational and cognitive dimensions. In doing so, we answer
Payne et al.’s (2011) call for research that considers antecedents of social capital. Additionally, we also investigate Adler and Kwon’s (2002) call for additional research exploring bureaucratic systems’ influence on social relationships.
Bureaucratic Systems’ Influence on Social Capital
Bureaucratic systems include various attributes of organizational structure and orientations that guide organizational action and can have a profound effect on the nature of
social relationships (Adler & Borys, 1996; Ouchi, 1980). Key features of bureaucratic
systems that influence social relationships include organizational formalization, continuity of employees in particular roles fostering greater specialization, and cooperative
orientations that encourage purposeful action and communication (e.g., Adler & Borys;
Barnard, 1938; Ouchi).
Formalization’s Effects on Trust and Shared Values
Formalization refers to an organization’s reliance on official rules to control behaviors
and decisions (Burns & Stalker, 1961). Formal procedures replace ad hoc ways of doing
business, allowing organizational members to form stable expectations regarding firm
activities, as well as create a basis for controlling organizational processes and monitoring employee actions (Adler & Borys, 1996; Burns & Stalker; Ouchi, 1980). For instance,
banks may have formal procedures for approving loans, altering product delivery
platforms, and offering packages or fee structures for SME customers in an attempt to
standardize various outputs.
Essential to the development of trust and shared values in what may be perceived
to be a risky relationship (Le & Nguyen, 2009) is socialization, close interaction, and an
understanding that one’s partner is motivated by goodwill or benevolence (Adler & Kwon,
2002; Granovetter, 1985). An organizational structure that enables flexibility beyond
role-prescribed behaviors can provide important insight into benevolent motives behind a
party’s actions (Adler & Borys, 1996; Ring & Van de Ven, 1994). For example, flexibility
and responsiveness to unique circumstances or client needs can demonstrate that a bank
May, 2013
627
is genuinely interested in a client’s success beyond the bank’s own self-interest (Doz,
1996; Rousseau, Sitkin, Burt, & Camerer, 1998).
Because SMEs are generally more dependent upon particular banks than large firms
with more financing options (Berger & Udell, 1998), bank responsiveness and interest in
the SME’s success is particularly salient. An SME’s attributions of a bank’s goodwill can
increase the social-psychological bonds between interfacing parties creating an important
foundation for trust (Doz, 1996). Additionally, close and flexible interactions between
parties create a basis for socialization (Mayo, 1945; Ouchi, 1980) which allows parties
to understand preferred ways of doing things, accept those ways as their own, and foster
shared values (Ring & Van de Ven, 1994). Therefore, bank bureaucratic structures that
allow for flexibility can create an atmosphere of trust and promote shared values with
their SME customers (Adler & Kwon, 2002). Alternatively, formalization by its nature
depersonalizes interaction (Burns & Stalker, 1961), which can reduce socialization that
supports shared values development and can alienate those interacting with highly
formalized organizations (Adler & Borys, 1996; Ouchi). Accordingly, we propose:
Hypothesis 1a: The degree of a bank’s formalization is negatively associated with
an SME’s trust in the bank.
Hypothesis 1b: The degree of a bank’s formalization is negatively associated with an
SME’s shared values with the bank.
Management Continuity’s Effects on Trust and Shared Values
Management continuity refers to the continuance of particular individuals within
specific organizational roles (Doz, 1996), which leads to greater employee specialization (March & Simon, 1958; Simon, 1945). That is, the longer an employee remains
in a particular organizational role, the deeper his or her knowledge and understanding
becomes regarding the nuances and context of organizational role responsibilities
(Barnard, 1938). Additionally, employee specialization is a key factor in bureaucratic
systems that affect the social nature of the organization (Adler & Borys, 1996; Ouchi,
1980). Within the realm of bank–SME relationships, management continuity refers to the
degree that there is a continuance of management on the part of the bank. More specifically, management continuity herein refers to the degree that the bank employee(s) who
interacts with a particular SME is consistent over time.
Doz (1996) argues that management continuity develops commitment to the relationship itself. Ring and Van de Ven (1994) also suggest that if interacting parties remain
constant through repeated cycles of exchange, interactions become more deeply socially
embedded and each party may come to believe that the other party understands their goals,
shares their values, and will act in accordance with concern for the relationship itself.
Affective bonds, shared goals, and concern for the relationship itself are each identified
as important underpinnings of trust (Ring & Van de Ven; Rousseau et al., 1998). Additionally, Mayo (1945) suggests that employment stability fosters socialization. Socialization toward common values requires consistent interaction over time where parties come
to recognize the values and goals of interacting parties and to accept these values and
goals as their own (Mayo). Therefore, if a bank maintains consistency in personnel, this
should foster the development of shared values between interfacing parties at the SME and
the bank. Thus we suggest:
Hypothesis 2a: The degree of a bank’s management continuity is positively associated
with an SME’s trust in the bank.
628
ENTREPRENEURSHIP THEORY and PRACTICE
Hypothesis 2b: The degree of a bank’s management continuity is positively associated with an SME’s shared values with the bank.
Customer Orientation’s Effects on Trust and Shared Values
Finally, bureaucratic systems can embody cooperative orientations (Barnard, 1938;
Ouchi, 1980; Simon, 1945). Such organizational cooperative orientations can induce
organizational members to continue their participation in the organization and promote
behaviors that facilitate attainment of joint goals. (Barnard; Ouchi). While this work has
focused on how internal orientations can induce organizational members to act toward
collective goals, organizational orientations can also foster cooperative action and loyalty
from important external partners (Das & Teng, 1998; Ring & Van de Ven, 1994). Indeed,
Saparito, Chen, and Sapienza (2004) found that bank customer orientation increased
customer firm loyalty. In particular, this systematic set of bank behaviors is designed to
build long-term relationships with SMEs (Haines, Riding, & Thomas, 1991; Saparito
et al.). Since we are focused on the interorganizational relationships between banks and
SMEs, we adopt Saparito et al.’s term of “customer orientation.”
Bank customer orientation is aimed at developing long-term customer relationships
through advice giving, attention, and responsiveness. Such activities develop expectations
of reciprocity and fair dealing that create social-psychological bonds (Granovetter, 1985;
Ring & Van de Ven, 1994) which are important to trust development (Rousseau et al.,
1998). Additionally, bank customer orientation enhances trust by encouraging communication and information sharing with SMEs through which the SME comes to better
understand the bank’s capabilities and dependability. This allows an SME to reflect on the
bank’s track record for role-related duties, which is an important element in assessing a
party’s trustworthiness (Granovetter).
A bank’s customer orientation should also foster the development of shared values.
Advice giving and helpfulness act as signals of goodwill and intimacy (Das & Teng, 1998)
which can enhance an SME’s perception of value congruence and identification with its
banking partner (Coleman, 1990; Granovetter, 1985). Further, a bank’s frequent dialogue
and interaction with SMEs can facilitate social-emotional relationships fostering positive
attributions about the bank’s moral integrity and goodwill, which are also important
elements fostering shared values (Coleman; Rousseau et al., 1998). Based upon this, we
propose the following two hypotheses:
Hypothesis 3a: The degree of a bank’s customer orientation is positively associated
with an SME’s trust in the bank.
Hypothesis 3b: The degree of a bank’s customer orientation is positively associated
with an SME’s shared values with the bank.
Methodology
We used a matched sample design of SMEs and the respective bank managers
responsible for each SME’s account. This design eliminated common-method bias by
using two separate sources to measure bank-level independent variables and customerlevel dependent variables. Our data collection included a three-part process. First, we
solicited banks in Connecticut, Missouri, New Jersey, and Pennsylvania. Of the 286 banks
within our sampling frame, 22 banks (7.7%) agreed to participate. There was no statistical
difference between the median total assets or the return on assets for banks that participated and for banks that did not.
May, 2013
629
Second, each bank compiled a complete list of SMEs with which the bank had both
deposit and lending relationships. Consistent with the U.S. Small Business Administration, SME customers were defined by a credit limit of up to $1 million. We randomly
distributed 7,298 surveys to these SMEs. Overall, 884 complete surveys were returned
for this research for a 12.1% usable response rate. The response rate is consistent with
similar studies with surveys of similar length (Haines et al., 1991; Lange, Warhuus, &
Levie, 1999).
Responding firms had a median age of 15 years, six full-time employees, annual
sales in the $500 thousand to $1 million range, and had conducted business with the
bank a median of 5 years. Since the surveys were anonymous, it was not possible to
calculate differences between respondents and nonrespondents. However, late respondents are considered similar to nonrespondents (Churchill, 1991). A two-tailed t-test
comparing early versus late respondents found no significant differences for any firm
variables.
Third, responding SME executives identified the bank manager primarily responsible
for the company’s account. Additionally, bank executives identified the bank manager
in charge of small business lending operations. We sent surveys to 263 bank managers,
assuring participation confidentiality, and they returned 217 surveys for an 82.5%
response rate. The result of this three-step sample design is 884 matched bank–SME
dyads. The 884 SMEs are nested within the 22 banks (range—23 to 65 SME respondents/
bank; median—44 SME respondents/bank).
Measures
Trust (Dependent Variable). We used Sapienza and Korsgaard’s (1996) 3-item trust
measure, adapted to reflect a banking context, and a 7-point scale (1 = very rarely true to
7 = very often true). We asked SMEs to rate: (1) The bank is honest in their dealings with
us; (2) We can trust the bank; (3) If the bank made a decision that was different from
what we would make, we would believe that the bank had good reasons for making this
decision (alpha = .88).
Shared Values (Dependent Variable). We adapted Tsai and Ghoshal’s (1998) 2-item
measure for shared values to reflect both an interorganizational and a banking context,
and used a 7-point scale (1 = very rarely true to 7 = very often true). SMEs rated two
statements: (1) We share common business values with the bank; (2) We feel that the
bank would act in a fashion consistent with what we would recommend without prior
discussion with us (alpha = .85).
Formalization (Independent Variable). We adapted Nohria and Ghoshal’s (1994) 3-item
measure to reflect the extent that banks employ formal rules and procedures in their
dealings with SMEs and a 7-point scale (1 = very infrequently to 7 = very frequently). We
asked bank managers to rate three statements as they related to their bank’s interaction
with SMEs: (1) Management provides a well-defined set of rules and procedures for
interaction with small business clients; (2) To the extent possible, there are manuals that
define the courses of action to be taken under different situations; (3) Central management
continuously monitors those employees that interact with clients to ensure that rules and
procedures are not violated (alpha = .76).
630
ENTREPRENEURSHIP THEORY and PRACTICE
Management Continuity (Independent Variable). We used Saparito et al.’s (2004)
3-item measure and a 7-point scale (1 = very infrequently to 7 = very frequently). We
asked bank managers to rate three statements as they related to the bank’s interaction with
SMEs: (1) One employee or a small team of employees handles a given small business
client’s accounts across various product and service lines; (2) Employees with direct client
interaction are rotated between branches and/or departments on a regular basis (reverse
coded); (3) There is low employee turnover among employees with direct small business
customer interaction (alpha = .72).
Customer Orientation (Independent Variable). We used Saparito et al.’s (2004) 4-item
measure and a 7-point scale (1 = very infrequently to 7 = very frequently). We asked bank
managers to rate three statements as they related to the bank’s interaction with SMEs: (1)
The bank encourages bank managers to play a helpful and advisory role with their small
business clients; (2) The bank encourages bank managers to act with significant flexibility
in meeting small business client borrowing and other financial needs; (3) The bank focuses
on improving bank–small business relationships by selling products that fit a specific
client’s needs; (4) The bank attempts to understand the business and marketplace of its
small business clients (alpha = .74).
Control Variables. Control variables included those known to affect bank–SME relationships. Bank market competitiveness influences the level of bank service and number
of banking alternatives (Berger & Udell, 1998; Petersen & Rajan, 1994). Therefore, we
included the U.S. Federal Reserve Bank’s Herfindahl–Hirschman index (HHI) bank
concentration index as a measure of bank market competitiveness (Petersen & Rajan).
Additionally, since the HHI is specific to different geographic markets, the index also acts
as an identifier of various local markets (Petersen & Rajan).
Since large banks are generally less involved with smaller loans, bank size (the
natural log of total assets reported in each bank’s 1999 annual report) was included
(Berger & Udell, 1998). Bank profitability influences the organization’s ability to extend
loans (Berger & Udell). Therefore, we measured bank profitability by bank return on
assets.
Both firm size and firm age have important implications for a firm’s ability to
accumulate many important intangible resources such as legitimacy and social connections that are important to social capital development (Adler & Kwon, 2002; Aldrich &
Auster, 1986). Consequently, we controlled for both factors. We measured firm size by
two factors—number of employees and sales revenues. Firm age was the number of years
that the SME had been in operation.
The banking relationship’s age and product breadth have significant influences on
the nature of the bank–firm relationship including social-psychological factors such
as commitment and trust (Saparito et al., 2004; Uzzi, 1999; Uzzi & Lancaster, 2003).
Consequently, we controlled for relationship age and number of accounts. We measured
relationship age by the number of years the SME conducted business with the bank. As a
measure of the breadth of the bank–SME relationship, we measured the number of
accounts the firm had with the bank. Whether or not a particular bank is a firm’s primary
banking institution influences a firm’s dependence on the bank (Uzzi). We measured the
main bank using a dummy variable (1 if the bank was the SME’s primary bank and 0 if
not). Finally, interfirm relationships are strongly influenced by perceptions of aligned
self-interest (Ring & Van de Ven, 1994; Saparito et al.). Thus, we controlled aligned
self-interest using Saparito et al.’s measure for self-interest assumptions. These data were
collected directly from the SME. Our model is presented in Figure 1.
May, 2013
631
Figure 1
Model of Hypothesized Relationships
Aggregation of Organizational-Level Variables
We used multiple bank managers as informed observers (Chen, Fahr, & MacMillan,
1993) to construct the bank-level independent variables. While aggregating employee
perceptions is a valid means to measure organizational-level variables, interrater reliabilities should be established (Chen et al.; Rousseau, 1985). We estimated rwg(j) statistics for
manager perceptions for bank-level constructs using procedures outlined in James,
Demaree, and Wolf (1993). This analysis yielded values indicating acceptable agreement
(i.e., above 0.70) for each aggregated bank-level variable (i.e., formalization, management
continuity, and customer orientation).
Model Estimation
We used hierarchical linear modeling (HLM) for hypothesis testing. HLM is appropriate because the data include multiple SME customers per bank. HLM is better than
632
ENTREPRENEURSHIP THEORY and PRACTICE
ordinary least squares (OLS) regression in nested group settings, where the observations
for each SME cannot be considered independent due to potential autocorrelation (Byrk &
Raudenbush, 1992). HLM corrects for potential autocorrelation and heteroscedasticity
and also reduces aggregation bias (Bloom & Milkovich, 1998). Although OLS generates
biased parameter estimates and standard errors when using multilevel data, it does provide
adequate effect size estimates and is therefore used to estimate model R2 to convey these
effect sizes (Wallace & Chen, 2006).
Results
Table 1 presents the means, standard deviations, and Pearson correlations for the
variables. Responding firms had a mean age of 21.1 years of operation and approximately
20 full-time employees, which is well under the 500 employee criteria for U.S. Small
Business Administration classification as a small firm. All variance inflation factors
were below 10 indicating there were no multicollinearity issues (Neter, Wasserman, &
Kunter, 1990).
Table 2 presents our regression results. Hypothesis 1a suggests a negative relationship
between formalization and trust. Results show formalization is significantly and negatively associated with trust supporting hypothesis 1a. Hypothesis 1b proposes a negative
relationship between formalization and shared values. As is shown in Table 2 (Model 4),
the coefficient for this variable is negative and significant providing support for hypothesis
1b.
According to hypothesis 2a, management continuity is positively associated with
trust. Results in Table 2 (Model 2) support hypothesis 2a showing that management
continuity is positively and significantly associated with trust. Hypothesis 2b suggests
management continuity and shared values are positively associated. As is shown in
Table 2 (Model 4), the coefficient for this variable is positive and significant providing
support for hypothesis 2b.
Hypothesis 3a predicted a positive relationship between a bank’s customer orientation
and trust. As results in Table 2 (Model 2) demonstrate, hypothesis 3a is supported. Lastly,
hypothesis 3b predicts a positive relationship between a bank’s customer orientation and
shared values. Results in Table 2 (Model 4) support hypothesis 3b. To summarize, all
hypotheses are supported.
Discussion
In response to calls for multilevel research and examinations of social capital as a
dependent variable (e.g., Adler & Kwon, 2002; Payne et al., 2011), our study makes a
focused contribution by extending our understanding of how bureaucratic systems influence social capital’s relational (i.e., trust) and cognitive (i.e., shared values) dimensions.
Our findings demonstrate that bank formalization is negatively associated with both
dimensions of social capital, while management continuity and customer orientation are
positively associated with both dimensions of social capital.
From both a research and practical perspective, understanding how bureaucratic
systems influence social relations is important because bureaucracy may have both
enabling and hindering effects on informal cooperation (Adler & Borys, 1996; Adler &
Kwon, 2002). Indeed, Adler and Borys suggest that bureaucratic systems that abrogate
employees’ abilities to act in accordance with their skills and understandings of unique
May, 2013
633
634
Table 1
Correlations, Means, and Standard Deviations†
ENTREPRENEURSHIP THEORY and PRACTICE
1. HHI§
2. Bank size‡
3. Bank ROA
4. SME age
5. SME employees
6. SME sales
7. Aligned self-interest
8. Relationship age
9. Number of accounts
10. Formalization
11. Management continuity
12. Customer orientation
13. Trust
14. Shared values
Mean
Standard deviation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
-0.08*
0.44**
0.03
-0.01
-0.05
0.02
-0.06
0.05
0.27**
0.06
-0.22**
0.01
-0.00
1,572.77
655.45
0.08*
0.01
0.14**
0.20**
0.04
-0.09**
-0.08*
0.27**
0.02
0.14**
-0.05
0.01
6.05
0.97
0.13**
0.10**
0.14**
0.10**
0.05
0.01
-0.01
-0.05
0.02
0.09**
0.10**
1.13
0.52
0.24**
0.21**
-0.01
0.35**
-0.06
0.05
0.05
-0.04
0.01
0.02
21.12
21.65
0.50**
0.05
0.03
-0.13**
0.08*
0.02
0.10**
0.00
0.03
19.95
41.44
0.09**
-0.03
-0.19**
0.17**
-0.01
0.14**
0.03
0.08*
3.34
1.84
-0.05
-0.03
-0.01
0.10**
0.08*
0.34**
0.41**
20.04
4.82
0.21**
-0.06
0.07*
-0.12**
0.01
-0.02
9.64
11.06
-0.14**
0.01
-0.09**
0.02
0.02
1.61
0.75
0.04
0.24**
-0.06
-0.04
11.92
1.51
0.25**
0.13**
0.13**
16.19
1.24
0.12**
0.15**
21.87
1.87
0.71**
17.63
3.44
10.64
2.65
* p < .05; ** p < .01
†
n = 884.
‡
Logarithm of total assets.
§
Coded as dummy variable with banking institution is primary financial institution = 1, not primary financial institution = 0.
HHI, Herfindahl–Hirschman index; ROA, return on assets; SME, small- and medium-sized enterprises.
Table 2
Hierarchical Regression Analysis Results for the Predictors of Trust and Shared
Values†‡
Trust
Variables
Model 1
HHI
bank size
Bank ROA
SME age
SME employees
SME sales
Aligned self-interest
Relationship age
Number of accounts
Formalization
Management continuity
Customer orientation
R2
DR2
-2 log-likelihood
Difference in c2
N
-0.00 (0.00)
-0.22 (0.18)
0.53 (0.35)
-0.00 (0.01)
-0.00 (0.00)
0.05 (0.07)
0.24*** (0.02)
0.01 (0.01)
0.10 (0.15)
0.13
4,645.57
884
Shared values
Model 2
-0.00 (0.00)
-0.20 (0.12)
0.56* (0.25)
-0.00 (0.01)
-0.00 (0.00)
0.03 (0.07)
0.24*** (0.02)
0.01 (0.01)
0.13 (0.15)
-0.17* (0.08)
0.22* (0.09)
0.31* (0.12)
0.15
0.02
4,636.03
9.54*
884
Model 3
-0.00 (0.00)
-0.04 (0.15)
0.41 (0.29)
0.00 (0.00)
-0.00 (0.00)
0.09+ (0.05)
0.22*** (0.02)
-0.00 (0.01)
0.12 (0.11)
0.19
4,121.47
884
Model 4
-0.00 (0.00)
-0.04 (0.11)
0.43+ (0.22)
0.00 (0.00)
-0.00 (0.00)
0.08 (0.05)
0.22*** (0.02)
-0.00 (0.01)
0.13 (0.11)
-0.13* (0.06)
0.15* (0.07)
0.26* (0.11)
0.21
0.02
4,111.56
9.91*
884
p < .10; * p < .05; ** p < .01; *** p < .001
Betas are unstandardized regression coefficients; standard errors are in parentheses.
Two-tailed tests.
HHI, Herfindahl–Hirschman index; ROA, return on assets; SME, small- and medium-sized enterprises.
+
†
‡
situations will negatively influence attitudes and social relationships, while bureaucratic
systems that leverage employees’ abilities and understandings will enhance attitudes and
social relationships. Our findings support these theoretical assertions. In compliance
with government oversight and to maintain objectivity, U.S. banks employ significant
formalized rules and closely monitor employees and customer transactions for compliance. Researchers assert that such reliance on rules and close monitoring will negatively
impact social relationships (Adler & Borys; Adler & Kwon). Our findings suggest that
bank formalization is negatively associated with social capital. While U.S. banks are
embedded in an institutional context that requires significant formalization, they do have
considerable freedom and control over their organization’s management continuity and
cooperative orientations. As we argued earlier, both of these factors should enable bank
employees to leverage their unique understandings of SME clients and respond in ways
to enhance the bank–SME relationship. Indeed, our findings show that both of these
factors enhance the development of social capital within bank–SME relationships.
We find these results particularly interesting given that neither of our controls of the
bank–firm relationship age or the relationship breadth (i.e., number of products) had any
statistically significant relationship with either social capital dimension. While both the
SME financing and the social capital literatures (e.g., Petersen & Rajan, 1994; Riding,
Haines, & Thomas, 1994; Uzzi, 1999; Uzzi & Lancaster, 2003) frequently use these
May, 2013
635
structural measures of relationships, we find in this study that it is the set of behaviors (i.e.,
formalized interaction, continuous contact with particular individuals, cooperative and
helpful interaction) that influences social capital development. This finding has potentially
important implications for structural measures of social capital if it is replicated in future
studies.
Limitations
This study uses cross-sectional survey data. Longitudinal data would add greater
confidence to our results and allow for stronger causal inferences regarding the nature of
the relationships between bureaucratic systems (i.e., formalization, employee continuity,
and customer orientation) and social capital (e.g., trust and shared values). A second
limitation is the lack of mutual data on trust and shared values. The challenge in doing so
is that it requires much greater access to and disclosure by both banks and their SME
clients. Finally, while our response rate is consistent with similar studies (e.g., Haines
et al., 1991; Lange et al., 1999), increasing the response rate would be beneficial.
Future Research and Conclusions
Although our results provide some evidence regarding antecedents of social capital in
SME–bank relationships, further research would provide a deeper understanding of these
relationships. For example, future research may investigate how SME–bank social capital
influences SME outcomes, such as how easy it is for SMEs to gain access to credit, and
what lending terms SMEs receive from their banks. For instance, shared values and trust
may ease access to credit and allow SMEs to negotiate better terms when borrowing from
their banks. Further, as our limitations suggest, researchers may collect longitudinal data
with which to examine the strength of our results during differing economic environments.
Additionally, as we noted, our data do not include mutual data on shared values and trust.
Thus, future research might help in understanding how banks’ shared values with their
SME customers, or the level of trust they have in their SME customers, might affect SME–
bank relationships or the outcomes of those relationships.
Second, while our research focused on the positive aspects of social capital within
the context of the bank–SME relationship, social capital has potential downsides (Edelman,
Bresnen, Newell, Scarbrough, & Swan, 2004). For instance, there is the potential for
overcommitment or loss of objectivity about partners in deeply embedded relationships
(Edelman et al.). This has particular import for the investor–SME context. Objective and
rational investment evaluation is an essential element to efficient debt markets (Berger &
Udell, 1998). Whether social capital in bank–SME relationships influences loan evaluation
objectivity would therefore be an interesting line of future research.
To conclude, social capital is a complex concept to understand and predict. Yet,
because of its use in a variety of researcher disciplines, we urge researchers to pursue other
antecedents relevant to their particular domains. Our research identifies three bureaucratic
controls important to social capital development in SME–bank relationships, but this is
only a first step for future research.
REFERENCES
Adler, P. & Borys, B. (1996). Two types of bureaucracy: Enabling and coercive. Administrative Science
Quarterly, 41, 61–89.
636
ENTREPRENEURSHIP THEORY and PRACTICE
Adler, P. & Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review,
27, 17–40.
Aldrich, H. & Auster, E.R. (1986). Even dwarfs started small: Liabilities of age and size and their strategic
implications. In B.M. Staw & L.L. Cummings (Eds.), Research in organizational behavior (Vol. 8,
pp. 165–198). Greenwich, CT: JAI Press.
Barnard, C. (1938). The functions of the executive. Cambridge, MA: Harvard University Press.
Berger, A. & Udell, G. (1998). The economics of small business finance: The roles of private equity and debt
markets in the financial growth cycle. Journal of Banking and Finance, 22, 613–673.
Bloom, M. & Milkovich, G.T. (1998). Relationships among risk, incentive pay, and organizational performance. Academy of Management Journal, 41, 283–297.
Burns, T. & Stalker, G. (1961). The management of innovation. London: Tavistock Publications.
Burt, R. (1992). Structural holes: The social structure of competition. Cambridge, MA: Harvard University
Press.
Byrk, A.S. & Raudenbush, S.W. (1992). Hierarchical linear models. Newbury Park, CA: Sage.
Chen, M., Fahr, J., & MacMillan, I. (1993). An exploration of the expertness of outside informants. Academy
of Management Journal, 36, 1614–1632.
Churchill, G.A. (1991). Marketing research: Methodological foundations. Chicago, IL: Dryden.
Coleman, J.S. (1990). Foundations of social theory. Cambridge, MA: Harvard University Press.
Das, T.K. & Teng, B.-S. (1998). Between trust and control: Developing confidence in partner cooperation in
alliances. Academy of Management Review, 23, 491–512.
Doz, Y.L. (1996). The evolution of cooperation in strategic alliances: Initial conditions or learning processes?
Strategic Management Journal, 17, 55–83.
Edelman, L., Bresnen, M., Newell, S., Scarbrough, H., & Swan, J. (2004). The benefits and pitfalls of social
capital: Empirical evidence from two organizations in the United Kingdom. British Journal of Management,
15, S59–S69.
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American
Journal of Sociology, 78, 1360–1380.
Haines, G., Riding, A., & Thomas, R. (1991). Small business bank shopping in Canada. Journal of Banking
and Finance, 15, 1041–1056.
James, L.R., Demaree, R.G., & Wolf, G. (1993). An assessment of within-group interrater agreement. Journal
of Applied Psychology, 78, 306–309.
Lange, J., Warhuus, J.P., & Levie, J. (1999). Entrepreneur/banker interaction in young growing firms: A large
scale international study. Frontiers of Entrepreneurship Research. Wellesley, MA: Center for Entrepreneurial
Research, Babson College.
Le, N. & Nguyen, T. (2009). The impact of networking on bank financing: The case of small and mediumsized enterprises in Vietnam. Entrepreneurship Theory and Practice, 33(4), 867–887.
March, J. & Simon, H. (1958). Organizations. New York: Wiley.
Mayo, E. (1945). The social problems of an industrial civilization. Cambridge, MA: Boston Division of
Research, Graduate School of Business, Harvard University.
May, 2013
637
Morse, E.A., Fowler, S.W., & Lawrence, T.B. (2007). The impact of virtual embeddedness on new venture
survival: Overcoming the liabilities of newness. Entrepreneurship Theory and Practice, 31(2), 139–159.
Nahapiet, J. & Ghoshal, S. (1998). Social capital, intellectual capital and the organizational advantage.
Academy of Management Review, 23, 242–266.
Neter, J., Wasserman, W., & Kunter, M.H. (1990). Applied statistical models (3rd ed.). Burr Ridge, IL:
Richard D. Irwin, Inc.
Nohria, N. & Ghoshal, S. (1994). Differentiated fit and shared values: Alternatives for managing headquarterssubsidiary relations. Strategic Management Journal, 15, 491–502.
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5, 14–37.
Ouchi, W.G. (1980). Markets, bureaucracies, and clans. Administrative Science Quarterly, 25, 129–141.
Packalen, K.A. (2007). Complementing capital: The role of status, demographic features, and social capital in
founding teams’ abilities to obtain resources. Entrepreneurship Theory and Practice, 31(6), 873–891.
Payne, G.T., Moore, C.B., Griffis, S.E., & Autry, C.W. (2011). Multilevel challenges and opportunities in
social capital research. Journal of Management, 37, 491–520.
Petersen, M. & Rajan, R. (1994). The benefits of firm-creditor relationships: Evidence from small business
data. Journal of Finance, 49, 3–37.
Portes, A. (1998). Social capital: Its origins and applications in modern sociology. Annual Review of
Sociology, 24, 1–24.
Riding, A., Haines, G., & Thomas, R. (1994). The Canadian small business-bank interface: A recursive model.
Entrepreneurship Theory and Practice, 18(4), 5–24.
Ring, P.S. & Van de Ven, A.H. (1994). Developmental processes of cooperative interorganizational relationships. Academy of Management Review, 19, 90–118.
Rousseau, D.M. (1985). Issues of level in organizational research. In B.M. Straw & L.L. Cummings (Eds.),
Research in organizational behavior (Vol. 7, pp. 1–37). Greenwich, CT: JAI Press.
Rousseau, D.M., Sitkin, S.B., Burt, R.S., & Camerer, C. (1998). Not so different after all: A cross-discipline
view of trust. Academy of Management Review, 23, 405–421.
Saparito, P., Chen, C., & Sapienza, H. (2004). The role of relational trust in bank-small firm relationships.
Academy of Management Journal, 47, 400–410.
Sapienza, H. & Korsgaard, M. (1996). The role of procedural justice in entrepreneur-venture capitalist capital
relations. Academy of Management Journal, 39, 544–574.
Shane, S. & Cable, D. (2002). Network ties, reputation, and the financing of new ventures. Management
Science, 48(3), 364–381.
Simon, H. (1945). Administrative behavior. New York: Free Press.
Tsai, W. & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy
of Management Journal, 41, 464–478.
Uzzi, B. (1999). Embeddedness in the making of financial capital: How social relations and networks benefit
firms seeking financing. American Sociological Review, 64, 481–505.
Uzzi, B. & Lancaster, R. (2003). Relational embeddedness and learning: The case of bank loan managers and
their clients. Management Science, 49, 383–399.
638
ENTREPRENEURSHIP THEORY and PRACTICE
Wallace, C. & Chen, G. (2006). A multilevel integration of personality, climate, self-regulation, and performance. Personnel Psychology, 59, 529–557.
Yli-Renko, H., Autio, E., & Sapienza, H. (2001). Social capital, knowledge acquisition, and knowledge
exploitation in young technology-based firms. Strategic Management Journal, 22, 587–613.
Zhang, J., Souitaris, V., Soh, P., & Wong, P. (2008). A contingent model of network utilization in early
financing of technology ventures. Entrepreneurship Theory and Practice, 32(4), 593–613.
Patrick A. Saparito is an Assistant Professor in the Department of Management at Saint Joseph’s University,
Philadelphia, PA, USA.
Joseph E. Coombs is an Associate Professor at Virginia Commonwealth University, Richmond, VA, USA.
The authors thank Duane Ireland and Luis Gomez-Mejia for their helpful comments on earlier drafts of this
manuscript.
May, 2013
639
© 2013 Baylor University
E T&P
Bureaucratic Systems’
Facilitating and
Hindering Influence
on Social Capital
Patrick A. Saparito
Joseph E. Coombs
This study demonstrates how banks’ bureaucratic systems (i.e., formalization, management
continuity, customer orientation) are associated with social capital’s relational and cognitive
dimensions. We collected survey data from a matched sample of 884 small- and mediumsized enterprises (SME) executives and 217 bank managers across 22 banks to test hypothesized relationships. Our results showed that formalization is negatively associated with
both dimensions of social capital, while management continuity and customer orientation
are positively associated with them. These results are a first step in answering calls in the
literature to study bureaucratic systems’ influence on social capital. Theoretical and future
research implications are discussed.
Introduction
Social capital plays an important role in investor–small- and medium-sized enterprise
(SME) relationships (Le & Nguyen, 2009; Sapienza & Korsgaard, 1996; Shane & Cable,
2002; Uzzi & Lancaster, 2003; Yli-Renko, Autio, & Sapienza, 2001). Social capital helps
increase investors’ information and understanding of SMEs (Yli-Renko et al.) resulting in
greater access to both equity and debt funding alike (Le & Nguyen; Shane & Cable; Uzzi
& Lancaster). While this important research examines social capital as an antecedent to
resource acquisition (i.e., knowledge, financial capital), little attention has been paid to the
antecedents of social capital within SME–investor relationships. Indeed, Payne, Moore,
Griffis, and Autry (2011) point out that over 90% of social capital research treats social
capital as an independent variable.
In practice, many banks struggle with configuring their bureaucratic systems
in attempts to enhance their client relationships with SMEs (Berger & Udell, 1998).
Researchers acknowledge the importance of bureaucratic systems’ influence on social
relationships (e.g., Adler & Kwon, 2002; Nahapiet & Ghoshal, 1998; Payne et al., 2011),
and indeed suggest this influence is “inevitable under conditions of repeated action”
Please send correspondence to: Patrick A. Saparito, tel.: 610-660-1157; e-mail: psaparit@sju.edu, and to
Joseph E. Coombs at jecoombs2@vcu.edu.
May, 2013
DOI: 10.1111/etap.12028
625
(Adler & Kwon, p. 19). Adler and Borys (1996) argue that whether the influence is
negative or positive is based upon whether or not bureaucratic systems depersonalize
interaction and attenuate employees’ abilities to develop unique understandings about the
task at hand. However, despite repeated calls for research that studies bureaucratic
systems’ influence on social relationships (e.g., Adler & Borys; Adler & Kwon; Nahapiet
& Ghoshal), little work has focused upon this relationship.
We respond directly to these calls and attempt to make a focused contribution to the
literature. In particular, our purpose is to examine how bank-level bureaucratic systems
influence social capital within bank–SME relationships. By doing so, our study takes the
rare steps of a multilevel approach and an examination of social capital as a dependent
variable (Payne et al., 2011). We test our hypotheses on a matched sample of 884 SME
executives and 217 managers across 22 banks. Data from bank managers measure the
bank-level bureaucratic systems (i.e., formalization, management continuity, and customer orientation), while data collected from SME executives measure social capital’s
relational (i.e., trust) and cognitive (i.e., shared values) dimensions. We conclude by
discussing our results and implications for future research.
Social Capital Dimensions
Adler and Kwon (2002, p. 23) define social capital as “the goodwill available to
individuals or groups.” The general intuition behind the concept of social capital is that
trust, expectations of reciprocity, and shared values and norms facilitate resource flows
and promote group action (Adler & Kwon; Nahapiet & Ghoshal, 1998). Social capital can
provide differential access to various resources and thereby be used for an individual’s
benefit and competitive advantage (Burt, 1992; Portes, 1998). For SMEs, social capital
can provide access to critical resources necessary for firm survival and growth (Morse,
Fowler, & Lawrence, 2007; Packalen, 2007).
The social capital literature has two primary research streams. The first locates social
capital’s source in the structure of a network’s social ties (Le & Nguyen, 2009; Zhang,
Souitaris, Soh, & Wong, 2008). For example, Coleman (1990) suggests that dense ties
within a collectivity foster self-enforcing norms facilitating the attainment of group goals.
The second research stream focuses on the content of specific ties (Adler & Kwon, 2002).
For instance, Uzzi (1999) found that trust-filled ties with banks facilitated an SME’s
access to credit, while Yli-Renko et al. (2001) reported that firm-trusting ties with venture
capitalists were associated with greater knowledge transfer. Consistent with research
examining investor–SME relationships (e.g., Uzzi; Uzzi & Lancaster, 2003; Yli-Renko
et al.), we focus on the content of specific ties.
Social capital is increasingly viewed as a multidimensional construct (Nahapiet &
Ghoshal, 1998; Tsai & Ghoshal, 1998). Nahapiet and Ghoshal identify three dimensions
of social capital: structural, relational, and cognitive. The structural dimension refers to
the pattern of network relationships. Network structure includes the existence or absence
of connections between a focal party and other actors (bridging approach) and the overall
pattern of relationships within a group (bonding approach). Thus, the structural dimension
reflects “the impersonal configuration of linkages between people and units” (Nahapiet &
Ghoshal, p. 244).
While the structural dimension focuses on the network structure of social relationships, Nahapiet and Ghoshal’s (1998) relational and cognitive dimensions focus on the
content of ties with specific actors. More specifically, the relational dimension refers to
the personal relationship between specific parties that develops over time (Granovetter,
626
ENTREPRENEURSHIP THEORY and PRACTICE
1985; Nahapiet & Ghoshal). Trust appears as the key attribute of the relational dimension
(Nahapiet & Ghoshal). In discussing the relational dimension, Nahapiet and Ghoshal’s
conceptualization of trust is based upon the notions of reciprocity and expected goodwill
that build strong interpersonal bonds. Trust enables sequential business interaction where
one party must act first with the expectation that the other party will fully respond and
uphold their commitments at a later time. Thus, trust acts as a social mechanism allowing
parties to take actions with confidence that future obligations will be fulfilled and vulnerabilities will not be exploited (Ouchi, 1980; Uzzi, 1999).
Finally, the cognitive dimension of social capital refers to shared values, interpretations, and systems of meaning among parties that provide a basis for making sense of
knowledge and classifying it into perceptual categories (Nahapiet & Ghoshal, 1998; Tsai
& Ghoshal, 1998). Shared values, interpretations, and systems of meaning facilitate
learning and knowledge transfer allowing individuals to share each other’s thinking
processes. These common understandings help individuals make sense of and interpret the
world around them (Nonaka, 1994). Consistent with research examining investor–SME
relationships, our focus is on the content of specific ties between parties. Consequently,
we focus on social capital’s relational and cognitive dimensions. In doing so, we answer
Payne et al.’s (2011) call for research that considers antecedents of social capital. Additionally, we also investigate Adler and Kwon’s (2002) call for additional research exploring bureaucratic systems’ influence on social relationships.
Bureaucratic Systems’ Influence on Social Capital
Bureaucratic systems include various attributes of organizational structure and orientations that guide organizational action and can have a profound effect on the nature of
social relationships (Adler & Borys, 1996; Ouchi, 1980). Key features of bureaucratic
systems that influence social relationships include organizational formalization, continuity of employees in particular roles fostering greater specialization, and cooperative
orientations that encourage purposeful action and communication (e.g., Adler & Borys;
Barnard, 1938; Ouchi).
Formalization’s Effects on Trust and Shared Values
Formalization refers to an organization’s reliance on official rules to control behaviors
and decisions (Burns & Stalker, 1961). Formal procedures replace ad hoc ways of doing
business, allowing organizational members to form stable expectations regarding firm
activities, as well as create a basis for controlling organizational processes and monitoring employee actions (Adler & Borys, 1996; Burns & Stalker; Ouchi, 1980). For instance,
banks may have formal procedures for approving loans, altering product delivery
platforms, and offering packages or fee structures for SME customers in an attempt to
standardize various outputs.
Essential to the development of trust and shared values in what may be perceived
to be a risky relationship (Le & Nguyen, 2009) is socialization, close interaction, and an
understanding that one’s partner is motivated by goodwill or benevolence (Adler & Kwon,
2002; Granovetter, 1985). An organizational structure that enables flexibility beyond
role-prescribed behaviors can provide important insight into benevolent motives behind a
party’s actions (Adler & Borys, 1996; Ring & Van de Ven, 1994). For example, flexibility
and responsiveness to unique circumstances or client needs can demonstrate that a bank
May, 2013
627
is genuinely interested in a client’s success beyond the bank’s own self-interest (Doz,
1996; Rousseau, Sitkin, Burt, & Camerer, 1998).
Because SMEs are generally more dependent upon particular banks than large firms
with more financing options (Berger & Udell, 1998), bank responsiveness and interest in
the SME’s success is particularly salient. An SME’s attributions of a bank’s goodwill can
increase the social-psychological bonds between interfacing parties creating an important
foundation for trust (Doz, 1996). Additionally, close and flexible interactions between
parties create a basis for socialization (Mayo, 1945; Ouchi, 1980) which allows parties
to understand preferred ways of doing things, accept those ways as their own, and foster
shared values (Ring & Van de Ven, 1994). Therefore, bank bureaucratic structures that
allow for flexibility can create an atmosphere of trust and promote shared values with
their SME customers (Adler & Kwon, 2002). Alternatively, formalization by its nature
depersonalizes interaction (Burns & Stalker, 1961), which can reduce socialization that
supports shared values development and can alienate those interacting with highly
formalized organizations (Adler & Borys, 1996; Ouchi). Accordingly, we propose:
Hypothesis 1a: The degree of a bank’s formalization is negatively associated with
an SME’s trust in the bank.
Hypothesis 1b: The degree of a bank’s formalization is negatively associated with an
SME’s shared values with the bank.
Management Continuity’s Effects on Trust and Shared Values
Management continuity refers to the continuance of particular individuals within
specific organizational roles (Doz, 1996), which leads to greater employee specialization (March & Simon, 1958; Simon, 1945). That is, the longer an employee remains
in a particular organizational role, the deeper his or her knowledge and understanding
becomes regarding the nuances and context of organizational role responsibilities
(Barnard, 1938). Additionally, employee specialization is a key factor in bureaucratic
systems that affect the social nature of the organization (Adler & Borys, 1996; Ouchi,
1980). Within the realm of bank–SME relationships, management continuity refers to the
degree that there is a continuance of management on the part of the bank. More specifically, management continuity herein refers to the degree that the bank employee(s) who
interacts with a particular SME is consistent over time.
Doz (1996) argues that management continuity develops commitment to the relationship itself. Ring and Van de Ven (1994) also suggest that if interacting parties remain
constant through repeated cycles of exchange, interactions become more deeply socially
embedded and each party may come to believe that the other party understands their goals,
shares their values, and will act in accordance with concern for the relationship itself.
Affective bonds, shared goals, and concern for the relationship itself are each identified
as important underpinnings of trust (Ring & Van de Ven; Rousseau et al., 1998). Additionally, Mayo (1945) suggests that employment stability fosters socialization. Socialization toward common values requires consistent interaction over time where parties come
to recognize the values and goals of interacting parties and to accept these values and
goals as their own (Mayo). Therefore, if a bank maintains consistency in personnel, this
should foster the development of shared values between interfacing parties at the SME and
the bank. Thus we suggest:
Hypothesis 2a: The degree of a bank’s management continuity is positively associated
with an SME’s trust in the bank.
628
ENTREPRENEURSHIP THEORY and PRACTICE
Hypothesis 2b: The degree of a bank’s management continuity is positively associated with an SME’s shared values with the bank.
Customer Orientation’s Effects on Trust and Shared Values
Finally, bureaucratic systems can embody cooperative orientations (Barnard, 1938;
Ouchi, 1980; Simon, 1945). Such organizational cooperative orientations can induce
organizational members to continue their participation in the organization and promote
behaviors that facilitate attainment of joint goals. (Barnard; Ouchi). While this work has
focused on how internal orientations can induce organizational members to act toward
collective goals, organizational orientations can also foster cooperative action and loyalty
from important external partners (Das & Teng, 1998; Ring & Van de Ven, 1994). Indeed,
Saparito, Chen, and Sapienza (2004) found that bank customer orientation increased
customer firm loyalty. In particular, this systematic set of bank behaviors is designed to
build long-term relationships with SMEs (Haines, Riding, & Thomas, 1991; Saparito
et al.). Since we are focused on the interorganizational relationships between banks and
SMEs, we adopt Saparito et al.’s term of “customer orientation.”
Bank customer orientation is aimed at developing long-term customer relationships
through advice giving, attention, and responsiveness. Such activities develop expectations
of reciprocity and fair dealing that create social-psychological bonds (Granovetter, 1985;
Ring & Van de Ven, 1994) which are important to trust development (Rousseau et al.,
1998). Additionally, bank customer orientation enhances trust by encouraging communication and information sharing with SMEs through which the SME comes to better
understand the bank’s capabilities and dependability. This allows an SME to reflect on the
bank’s track record for role-related duties, which is an important element in assessing a
party’s trustworthiness (Granovetter).
A bank’s customer orientation should also foster the development of shared values.
Advice giving and helpfulness act as signals of goodwill and intimacy (Das & Teng, 1998)
which can enhance an SME’s perception of value congruence and identification with its
banking partner (Coleman, 1990; Granovetter, 1985). Further, a bank’s frequent dialogue
and interaction with SMEs can facilitate social-emotional relationships fostering positive
attributions about the bank’s moral integrity and goodwill, which are also important
elements fostering shared values (Coleman; Rousseau et al., 1998). Based upon this, we
propose the following two hypotheses:
Hypothesis 3a: The degree of a bank’s customer orientation is positively associated
with an SME’s trust in the bank.
Hypothesis 3b: The degree of a bank’s customer orientation is positively associated
with an SME’s shared values with the bank.
Methodology
We used a matched sample design of SMEs and the respective bank managers
responsible for each SME’s account. This design eliminated common-method bias by
using two separate sources to measure bank-level independent variables and customerlevel dependent variables. Our data collection included a three-part process. First, we
solicited banks in Connecticut, Missouri, New Jersey, and Pennsylvania. Of the 286 banks
within our sampling frame, 22 banks (7.7%) agreed to participate. There was no statistical
difference between the median total assets or the return on assets for banks that participated and for banks that did not.
May, 2013
629
Second, each bank compiled a complete list of SMEs with which the bank had both
deposit and lending relationships. Consistent with the U.S. Small Business Administration, SME customers were defined by a credit limit of up to $1 million. We randomly
distributed 7,298 surveys to these SMEs. Overall, 884 complete surveys were returned
for this research for a 12.1% usable response rate. The response rate is consistent with
similar studies with surveys of similar length (Haines et al., 1991; Lange, Warhuus, &
Levie, 1999).
Responding firms had a median age of 15 years, six full-time employees, annual
sales in the $500 thousand to $1 million range, and had conducted business with the
bank a median of 5 years. Since the surveys were anonymous, it was not possible to
calculate differences between respondents and nonrespondents. However, late respondents are considered similar to nonrespondents (Churchill, 1991). A two-tailed t-test
comparing early versus late respondents found no significant differences for any firm
variables.
Third, responding SME executives identified the bank manager primarily responsible
for the company’s account. Additionally, bank executives identified the bank manager
in charge of small business lending operations. We sent surveys to 263 bank managers,
assuring participation confidentiality, and they returned 217 surveys for an 82.5%
response rate. The result of this three-step sample design is 884 matched bank–SME
dyads. The 884 SMEs are nested within the 22 banks (range—23 to 65 SME respondents/
bank; median—44 SME respondents/bank).
Measures
Trust (Dependent Variable). We used Sapienza and Korsgaard’s (1996) 3-item trust
measure, adapted to reflect a banking context, and a 7-point scale (1 = very rarely true to
7 = very often true). We asked SMEs to rate: (1) The bank is honest in their dealings with
us; (2) We can trust the bank; (3) If the bank made a decision that was different from
what we would make, we would believe that the bank had good reasons for making this
decision (alpha = .88).
Shared Values (Dependent Variable). We adapted Tsai and Ghoshal’s (1998) 2-item
measure for shared values to reflect both an interorganizational and a banking context,
and used a 7-point scale (1 = very rarely true to 7 = very often true). SMEs rated two
statements: (1) We share common business values with the bank; (2) We feel that the
bank would act in a fashion consistent with what we would recommend without prior
discussion with us (alpha = .85).
Formalization (Independent Variable). We adapted Nohria and Ghoshal’s (1994) 3-item
measure to reflect the extent that banks employ formal rules and procedures in their
dealings with SMEs and a 7-point scale (1 = very infrequently to 7 = very frequently). We
asked bank managers to rate three statements as they related to their bank’s interaction
with SMEs: (1) Management provides a well-defined set of rules and procedures for
interaction with small business clients; (2) To the extent possible, there are manuals that
define the courses of action to be taken under different situations; (3) Central management
continuously monitors those employees that interact with clients to ensure that rules and
procedures are not violated (alpha = .76).
630
ENTREPRENEURSHIP THEORY and PRACTICE
Management Continuity (Independent Variable). We used Saparito et al.’s (2004)
3-item measure and a 7-point scale (1 = very infrequently to 7 = very frequently). We
asked bank managers to rate three statements as they related to the bank’s interaction with
SMEs: (1) One employee or a small team of employees handles a given small business
client’s accounts across various product and service lines; (2) Employees with direct client
interaction are rotated between branches and/or departments on a regular basis (reverse
coded); (3) There is low employee turnover among employees with direct small business
customer interaction (alpha = .72).
Customer Orientation (Independent Variable). We used Saparito et al.’s (2004) 4-item
measure and a 7-point scale (1 = very infrequently to 7 = very frequently). We asked bank
managers to rate three statements as they related to the bank’s interaction with SMEs: (1)
The bank encourages bank managers to play a helpful and advisory role with their small
business clients; (2) The bank encourages bank managers to act with significant flexibility
in meeting small business client borrowing and other financial needs; (3) The bank focuses
on improving bank–small business relationships by selling products that fit a specific
client’s needs; (4) The bank attempts to understand the business and marketplace of its
small business clients (alpha = .74).
Control Variables. Control variables included those known to affect bank–SME relationships. Bank market competitiveness influences the level of bank service and number
of banking alternatives (Berger & Udell, 1998; Petersen & Rajan, 1994). Therefore, we
included the U.S. Federal Reserve Bank’s Herfindahl–Hirschman index (HHI) bank
concentration index as a measure of bank market competitiveness (Petersen & Rajan).
Additionally, since the HHI is specific to different geographic markets, the index also acts
as an identifier of various local markets (Petersen & Rajan).
Since large banks are generally less involved with smaller loans, bank size (the
natural log of total assets reported in each bank’s 1999 annual report) was included
(Berger & Udell, 1998). Bank profitability influences the organization’s ability to extend
loans (Berger & Udell). Therefore, we measured bank profitability by bank return on
assets.
Both firm size and firm age have important implications for a firm’s ability to
accumulate many important intangible resources such as legitimacy and social connections that are important to social capital development (Adler & Kwon, 2002; Aldrich &
Auster, 1986). Consequently, we controlled for both factors. We measured firm size by
two factors—number of employees and sales revenues. Firm age was the number of years
that the SME had been in operation.
The banking relationship’s age and product breadth have significant influences on
the nature of the bank–firm relationship including social-psychological factors such
as commitment and trust (Saparito et al., 2004; Uzzi, 1999; Uzzi & Lancaster, 2003).
Consequently, we controlled for relationship age and number of accounts. We measured
relationship age by the number of years the SME conducted business with the bank. As a
measure of the breadth of the bank–SME relationship, we measured the number of
accounts the firm had with the bank. Whether or not a particular bank is a firm’s primary
banking institution influences a firm’s dependence on the bank (Uzzi). We measured the
main bank using a dummy variable (1 if the bank was the SME’s primary bank and 0 if
not). Finally, interfirm relationships are strongly influenced by perceptions of aligned
self-interest (Ring & Van de Ven, 1994; Saparito et al.). Thus, we controlled aligned
self-interest using Saparito et al.’s measure for self-interest assumptions. These data were
collected directly from the SME. Our model is presented in Figure 1.
May, 2013
631
Figure 1
Model of Hypothesized Relationships
Aggregation of Organizational-Level Variables
We used multiple bank managers as informed observers (Chen, Fahr, & MacMillan,
1993) to construct the bank-level independent variables. While aggregating employee
perceptions is a valid means to measure organizational-level variables, interrater reliabilities should be established (Chen et al.; Rousseau, 1985). We estimated rwg(j) statistics for
manager perceptions for bank-level constructs using procedures outlined in James,
Demaree, and Wolf (1993). This analysis yielded values indicating acceptable agreement
(i.e., above 0.70) for each aggregated bank-level variable (i.e., formalization, management
continuity, and customer orientation).
Model Estimation
We used hierarchical linear modeling (HLM) for hypothesis testing. HLM is appropriate because the data include multiple SME customers per bank. HLM is better than
632
ENTREPRENEURSHIP THEORY and PRACTICE
ordinary least squares (OLS) regression in nested group settings, where the observations
for each SME cannot be considered independent due to potential autocorrelation (Byrk &
Raudenbush, 1992). HLM corrects for potential autocorrelation and heteroscedasticity
and also reduces aggregation bias (Bloom & Milkovich, 1998). Although OLS generates
biased parameter estimates and standard errors when using multilevel data, it does provide
adequate effect size estimates and is therefore used to estimate model R2 to convey these
effect sizes (Wallace & Chen, 2006).
Results
Table 1 presents the means, standard deviations, and Pearson correlations for the
variables. Responding firms had a mean age of 21.1 years of operation and approximately
20 full-time employees, which is well under the 500 employee criteria for U.S. Small
Business Administration classification as a small firm. All variance inflation factors
were below 10 indicating there were no multicollinearity issues (Neter, Wasserman, &
Kunter, 1990).
Table 2 presents our regression results. Hypothesis 1a suggests a negative relationship
between formalization and trust. Results show formalization is significantly and negatively associated with trust supporting hypothesis 1a. Hypothesis 1b proposes a negative
relationship between formalization and shared values. As is shown in Table 2 (Model 4),
the coefficient for this variable is negative and significant providing support for hypothesis
1b.
According to hypothesis 2a, management continuity is positively associated with
trust. Results in Table 2 (Model 2) support hypothesis 2a showing that management
continuity is positively and significantly associated with trust. Hypothesis 2b suggests
management continuity and shared values are positively associated. As is shown in
Table 2 (Model 4), the coefficient for this variable is positive and significant providing
support for hypothesis 2b.
Hypothesis 3a predicted a positive relationship between a bank’s customer orientation
and trust. As results in Table 2 (Model 2) demonstrate, hypothesis 3a is supported. Lastly,
hypothesis 3b predicts a positive relationship between a bank’s customer orientation and
shared values. Results in Table 2 (Model 4) support hypothesis 3b. To summarize, all
hypotheses are supported.
Discussion
In response to calls for multilevel research and examinations of social capital as a
dependent variable (e.g., Adler & Kwon, 2002; Payne et al., 2011), our study makes a
focused contribution by extending our understanding of how bureaucratic systems influence social capital’s relational (i.e., trust) and cognitive (i.e., shared values) dimensions.
Our findings demonstrate that bank formalization is negatively associated with both
dimensions of social capital, while management continuity and customer orientation are
positively associated with both dimensions of social capital.
From both a research and practical perspective, understanding how bureaucratic
systems influence social relations is important because bureaucracy may have both
enabling and hindering effects on informal cooperation (Adler & Borys, 1996; Adler &
Kwon, 2002). Indeed, Adler and Borys suggest that bureaucratic systems that abrogate
employees’ abilities to act in accordance with their skills and understandings of unique
May, 2013
633
634
Table 1
Correlations, Means, and Standard Deviations†
ENTREPRENEURSHIP THEORY and PRACTICE
1. HHI§
2. Bank size‡
3. Bank ROA
4. SME age
5. SME employees
6. SME sales
7. Aligned self-interest
8. Relationship age
9. Number of accounts
10. Formalization
11. Management continuity
12. Customer orientation
13. Trust
14. Shared values
Mean
Standard deviation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
-0.08*
0.44**
0.03
-0.01
-0.05
0.02
-0.06
0.05
0.27**
0.06
-0.22**
0.01
-0.00
1,572.77
655.45
0.08*
0.01
0.14**
0.20**
0.04
-0.09**
-0.08*
0.27**
0.02
0.14**
-0.05
0.01
6.05
0.97
0.13**
0.10**
0.14**
0.10**
0.05
0.01
-0.01
-0.05
0.02
0.09**
0.10**
1.13
0.52
0.24**
0.21**
-0.01
0.35**
-0.06
0.05
0.05
-0.04
0.01
0.02
21.12
21.65
0.50**
0.05
0.03
-0.13**
0.08*
0.02
0.10**
0.00
0.03
19.95
41.44
0.09**
-0.03
-0.19**
0.17**
-0.01
0.14**
0.03
0.08*
3.34
1.84
-0.05
-0.03
-0.01
0.10**
0.08*
0.34**
0.41**
20.04
4.82
0.21**
-0.06
0.07*
-0.12**
0.01
-0.02
9.64
11.06
-0.14**
0.01
-0.09**
0.02
0.02
1.61
0.75
0.04
0.24**
-0.06
-0.04
11.92
1.51
0.25**
0.13**
0.13**
16.19
1.24
0.12**
0.15**
21.87
1.87
0.71**
17.63
3.44
10.64
2.65
* p < .05; ** p < .01
†
n = 884.
‡
Logarithm of total assets.
§
Coded as dummy variable with banking institution is primary financial institution = 1, not primary financial institution = 0.
HHI, Herfindahl–Hirschman index; ROA, return on assets; SME, small- and medium-sized enterprises.
Table 2
Hierarchical Regression Analysis Results for the Predictors of Trust and Shared
Values†‡
Trust
Variables
Model 1
HHI
bank size
Bank ROA
SME age
SME employees
SME sales
Aligned self-interest
Relationship age
Number of accounts
Formalization
Management continuity
Customer orientation
R2
DR2
-2 log-likelihood
Difference in c2
N
-0.00 (0.00)
-0.22 (0.18)
0.53 (0.35)
-0.00 (0.01)
-0.00 (0.00)
0.05 (0.07)
0.24*** (0.02)
0.01 (0.01)
0.10 (0.15)
0.13
4,645.57
884
Shared values
Model 2
-0.00 (0.00)
-0.20 (0.12)
0.56* (0.25)
-0.00 (0.01)
-0.00 (0.00)
0.03 (0.07)
0.24*** (0.02)
0.01 (0.01)
0.13 (0.15)
-0.17* (0.08)
0.22* (0.09)
0.31* (0.12)
0.15
0.02
4,636.03
9.54*
884
Model 3
-0.00 (0.00)
-0.04 (0.15)
0.41 (0.29)
0.00 (0.00)
-0.00 (0.00)
0.09+ (0.05)
0.22*** (0.02)
-0.00 (0.01)
0.12 (0.11)
0.19
4,121.47
884
Model 4
-0.00 (0.00)
-0.04 (0.11)
0.43+ (0.22)
0.00 (0.00)
-0.00 (0.00)
0.08 (0.05)
0.22*** (0.02)
-0.00 (0.01)
0.13 (0.11)
-0.13* (0.06)
0.15* (0.07)
0.26* (0.11)
0.21
0.02
4,111.56
9.91*
884
p < .10; * p < .05; ** p < .01; *** p < .001
Betas are unstandardized regression coefficients; standard errors are in parentheses.
Two-tailed tests.
HHI, Herfindahl–Hirschman index; ROA, return on assets; SME, small- and medium-sized enterprises.
+
†
‡
situations will negatively influence attitudes and social relationships, while bureaucratic
systems that leverage employees’ abilities and understandings will enhance attitudes and
social relationships. Our findings support these theoretical assertions. In compliance
with government oversight and to maintain objectivity, U.S. banks employ significant
formalized rules and closely monitor employees and customer transactions for compliance. Researchers assert that such reliance on rules and close monitoring will negatively
impact social relationships (Adler & Borys; Adler & Kwon). Our findings suggest that
bank formalization is negatively associated with social capital. While U.S. banks are
embedded in an institutional context that requires significant formalization, they do have
considerable freedom and control over their organization’s management continuity and
cooperative orientations. As we argued earlier, both of these factors should enable bank
employees to leverage their unique understandings of SME clients and respond in ways
to enhance the bank–SME relationship. Indeed, our findings show that both of these
factors enhance the development of social capital within bank–SME relationships.
We find these results particularly interesting given that neither of our controls of the
bank–firm relationship age or the relationship breadth (i.e., number of products) had any
statistically significant relationship with either social capital dimension. While both the
SME financing and the social capital literatures (e.g., Petersen & Rajan, 1994; Riding,
Haines, & Thomas, 1994; Uzzi, 1999; Uzzi & Lancaster, 2003) frequently use these
May, 2013
635
structural measures of relationships, we find in this study that it is the set of behaviors (i.e.,
formalized interaction, continuous contact with particular individuals, cooperative and
helpful interaction) that influences social capital development. This finding has potentially
important implications for structural measures of social capital if it is replicated in future
studies.
Limitations
This study uses cross-sectional survey data. Longitudinal data would add greater
confidence to our results and allow for stronger causal inferences regarding the nature of
the relationships between bureaucratic systems (i.e., formalization, employee continuity,
and customer orientation) and social capital (e.g., trust and shared values). A second
limitation is the lack of mutual data on trust and shared values. The challenge in doing so
is that it requires much greater access to and disclosure by both banks and their SME
clients. Finally, while our response rate is consistent with similar studies (e.g., Haines
et al., 1991; Lange et al., 1999), increasing the response rate would be beneficial.
Future Research and Conclusions
Although our results provide some evidence regarding antecedents of social capital in
SME–bank relationships, further research would provide a deeper understanding of these
relationships. For example, future research may investigate how SME–bank social capital
influences SME outcomes, such as how easy it is for SMEs to gain access to credit, and
what lending terms SMEs receive from their banks. For instance, shared values and trust
may ease access to credit and allow SMEs to negotiate better terms when borrowing from
their banks. Further, as our limitations suggest, researchers may collect longitudinal data
with which to examine the strength of our results during differing economic environments.
Additionally, as we noted, our data do not include mutual data on shared values and trust.
Thus, future research might help in understanding how banks’ shared values with their
SME customers, or the level of trust they have in their SME customers, might affect SME–
bank relationships or the outcomes of those relationships.
Second, while our research focused on the positive aspects of social capital within
the context of the bank–SME relationship, social capital has potential downsides (Edelman,
Bresnen, Newell, Scarbrough, & Swan, 2004). For instance, there is the potential for
overcommitment or loss of objectivity about partners in deeply embedded relationships
(Edelman et al.). This has particular import for the investor–SME context. Objective and
rational investment evaluation is an essential element to efficient debt markets (Berger &
Udell, 1998). Whether social capital in bank–SME relationships influences loan evaluation
objectivity would therefore be an interesting line of future research.
To conclude, social capital is a complex concept to understand and predict. Yet,
because of its use in a variety of researcher disciplines, we urge researchers to pursue other
antecedents relevant to their particular domains. Our research identifies three bureaucratic
controls important to social capital development in SME–bank relationships, but this is
only a first step for future research.
REFERENCES
Adler, P. & Borys, B. (1996). Two types of bureaucracy: Enabling and coercive. Administrative Science
Quarterly, 41, 61–89.
636
ENTREPRENEURSHIP THEORY and PRACTICE
Adler, P. & Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review,
27, 17–40.
Aldrich, H. & Auster, E.R. (1986). Even dwarfs started small: Liabilities of age and size and their strategic
implications. In B.M. Staw & L.L. Cummings (Eds.), Research in organizational behavior (Vol. 8,
pp. 165–198). Greenwich, CT: JAI Press.
Barnard, C. (1938). The functions of the executive. Cambridge, MA: Harvard University Press.
Berger, A. & Udell, G. (1998). The economics of small business finance: The roles of private equity and debt
markets in the financial growth cycle. Journal of Banking and Finance, 22, 613–673.
Bloom, M. & Milkovich, G.T. (1998). Relationships among risk, incentive pay, and organizational performance. Academy of Management Journal, 41, 283–297.
Burns, T. & Stalker, G. (1961). The management of innovation. London: Tavistock Publications.
Burt, R. (1992). Structural holes: The social structure of competition. Cambridge, MA: Harvard University
Press.
Byrk, A.S. & Raudenbush, S.W. (1992). Hierarchical linear models. Newbury Park, CA: Sage.
Chen, M., Fahr, J., & MacMillan, I. (1993). An exploration of the expertness of outside informants. Academy
of Management Journal, 36, 1614–1632.
Churchill, G.A. (1991). Marketing research: Methodological foundations. Chicago, IL: Dryden.
Coleman, J.S. (1990). Foundations of social theory. Cambridge, MA: Harvard University Press.
Das, T.K. & Teng, B.-S. (1998). Between trust and control: Developing confidence in partner cooperation in
alliances. Academy of Management Review, 23, 491–512.
Doz, Y.L. (1996). The evolution of cooperation in strategic alliances: Initial conditions or learning processes?
Strategic Management Journal, 17, 55–83.
Edelman, L., Bresnen, M., Newell, S., Scarbrough, H., & Swan, J. (2004). The benefits and pitfalls of social
capital: Empirical evidence from two organizations in the United Kingdom. British Journal of Management,
15, S59–S69.
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American
Journal of Sociology, 78, 1360–1380.
Haines, G., Riding, A., & Thomas, R. (1991). Small business bank shopping in Canada. Journal of Banking
and Finance, 15, 1041–1056.
James, L.R., Demaree, R.G., & Wolf, G. (1993). An assessment of within-group interrater agreement. Journal
of Applied Psychology, 78, 306–309.
Lange, J., Warhuus, J.P., & Levie, J. (1999). Entrepreneur/banker interaction in young growing firms: A large
scale international study. Frontiers of Entrepreneurship Research. Wellesley, MA: Center for Entrepreneurial
Research, Babson College.
Le, N. & Nguyen, T. (2009). The impact of networking on bank financing: The case of small and mediumsized enterprises in Vietnam. Entrepreneurship Theory and Practice, 33(4), 867–887.
March, J. & Simon, H. (1958). Organizations. New York: Wiley.
Mayo, E. (1945). The social problems of an industrial civilization. Cambridge, MA: Boston Division of
Research, Graduate School of Business, Harvard University.
May, 2013
637
Morse, E.A., Fowler, S.W., & Lawrence, T.B. (2007). The impact of virtual embeddedness on new venture
survival: Overcoming the liabilities of newness. Entrepreneurship Theory and Practice, 31(2), 139–159.
Nahapiet, J. & Ghoshal, S. (1998). Social capital, intellectual capital and the organizational advantage.
Academy of Management Review, 23, 242–266.
Neter, J., Wasserman, W., & Kunter, M.H. (1990). Applied statistical models (3rd ed.). Burr Ridge, IL:
Richard D. Irwin, Inc.
Nohria, N. & Ghoshal, S. (1994). Differentiated fit and shared values: Alternatives for managing headquarterssubsidiary relations. Strategic Management Journal, 15, 491–502.
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5, 14–37.
Ouchi, W.G. (1980). Markets, bureaucracies, and clans. Administrative Science Quarterly, 25, 129–141.
Packalen, K.A. (2007). Complementing capital: The role of status, demographic features, and social capital in
founding teams’ abilities to obtain resources. Entrepreneurship Theory and Practice, 31(6), 873–891.
Payne, G.T., Moore, C.B., Griffis, S.E., & Autry, C.W. (2011). Multilevel challenges and opportunities in
social capital research. Journal of Management, 37, 491–520.
Petersen, M. & Rajan, R. (1994). The benefits of firm-creditor relationships: Evidence from small business
data. Journal of Finance, 49, 3–37.
Portes, A. (1998). Social capital: Its origins and applications in modern sociology. Annual Review of
Sociology, 24, 1–24.
Riding, A., Haines, G., & Thomas, R. (1994). The Canadian small business-bank interface: A recursive model.
Entrepreneurship Theory and Practice, 18(4), 5–24.
Ring, P.S. & Van de Ven, A.H. (1994). Developmental processes of cooperative interorganizational relationships. Academy of Management Review, 19, 90–118.
Rousseau, D.M. (1985). Issues of level in organizational research. In B.M. Straw & L.L. Cummings (Eds.),
Research in organizational behavior (Vol. 7, pp. 1–37). Greenwich, CT: JAI Press.
Rousseau, D.M., Sitkin, S.B., Burt, R.S., & Camerer, C. (1998). Not so different after all: A cross-discipline
view of trust. Academy of Management Review, 23, 405–421.
Saparito, P., Chen, C., & Sapienza, H. (2004). The role of relational trust in bank-small firm relationships.
Academy of Management Journal, 47, 400–410.
Sapienza, H. & Korsgaard, M. (1996). The role of procedural justice in entrepreneur-venture capitalist capital
relations. Academy of Management Journal, 39, 544–574.
Shane, S. & Cable, D. (2002). Network ties, reputation, and the financing of new ventures. Management
Science, 48(3), 364–381.
Simon, H. (1945). Administrative behavior. New York: Free Press.
Tsai, W. & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy
of Management Journal, 41, 464–478.
Uzzi, B. (1999). Embeddedness in the making of financial capital: How social relations and networks benefit
firms seeking financing. American Sociological Review, 64, 481–505.
Uzzi, B. & Lancaster, R. (2003). Relational embeddedness and learning: The case of bank loan managers and
their clients. Management Science, 49, 383–399.
638
ENTREPRENEURSHIP THEORY and PRACTICE
Wallace, C. & Chen, G. (2006). A multilevel integration of personality, climate, self-regulation, and performance. Personnel Psychology, 59, 529–557.
Yli-Renko, H., Autio, E., & Sapienza, H. (2001). Social capital, knowledge acquisition, and knowledge
exploitation in young technology-based firms. Strategic Management Journal, 22, 587–613.
Zhang, J., Souitaris, V., Soh, P., & Wong, P. (2008). A contingent model of network utilization in early
financing of technology ventures. Entrepreneurship Theory and Practice, 32(4), 593–613.
Patrick A. Saparito is an Assistant Professor in the Department of Management at Saint Joseph’s University,
Philadelphia, PA, USA.
Joseph E. Coombs is an Associate Professor at Virginia Commonwealth University, Richmond, VA, USA.
The authors thank Duane Ireland and Luis Gomez-Mejia for their helpful comments on earlier drafts of this
manuscript.
May, 2013
639