Study on the Efficiency of SMEs’ Bank Financing in Clusters 159
of the firm though inter-person relationships [6]. It shows
that a high level of inter-person relationship contributes
to businesses’ bank financing and played a role in the
financing process. Therefore, we assume that:
H1 The higher the level of inter-person relationship,
the higher the level of enterprise bank financing per-
formance.
2.2. Inter-firm Relationship and Bank Financing
High level of inter-firm relationships means that they do
not try to solve the problem in the process of damaging
each other's interests [7]. They do not care gain or loss in
the collaboration or have opportunistic behaviors. High
level of inter-firm relationship shows good performance
and partner history of the two sides and further improv-
ing the companies’ financial efficiency from banks [8].
Actually, mutual trusted businesses will pay extra efforts
to overcome difficulties and help each other to solve
problems because they understand the situation of each
other and have full information, so the good credit is
more likely to occur [9]. The more stable the long-term
oriented trade relationship between enterprises, the more
opportunities of external financing, the more possibilities
of enterprises’ getting financial resources from the bank.
Therefore, we assume that:
H2 The higher the level of inter-firm relationship, the
higher the level of enterprise bank financing perform-
ance.
3. Research Method
3.1. Sample and Data Collection
This paper uses statistical tool to analyze the model and
also based on through the literature review, expert con-
sultation and semi-open questionnaires, etc. Before
sending out the questionnaires, we will consult three ex-
perts about the description methods of questions and
contents, adjusting the questionnaire mainly from theo-
retical viewpoint and long-term management and con-
sulting experience. We elect several enterprises to do
further evaluation and interviews, consulting senior ex-
ecutives and in-depth interviews, and form the final
questionnaire used in this study.
On this basis, this research cooperates with Private
Enterprises Business Association in Wenzhou, Zhejiang
Province. We selected 700 companies randomly from the
Association's Business Directory, sent out700 question-
naires from early October 2007 to the end of 2008, and
collected 305 questionnaires back, reaching 43.5%.In the
returned questionnaires, there were 94 with incomplete
content or obvious errors and be removed as invalid
questionnaires. The 211 valid questionnaires were effec-
tive response, with a valid rate of 30.1%. In order to en-
sure that data does not exist non-response bias, we do
Chi-square analysis to early and late recovery question-
naire in the enterprise's employee number and sales
revenues. The result shows that the questionnaire in the
two groups has no significant difference, indicating that
the data was not significant non-response bias. Ta b le 1 is
the statistical analysis of sample firm business sales.
3.2. Measurement
This measurement uses the 5-point scale table. Accord-
ing to the actual situation and the degree of consistency
from "totally disagree" to "completely agree", respon-
dents give scores from 1 to 5. In order to avoid the prob-
lems, this study Harman single-factor test. The method is
to use all items in factor analysis, without rotation by
getting the first principal component, which reflects the
amount of CMV. In this article, all questionnaire items
(independent variables and dependent variables) are used
in factor analysis; five factors explained 56% of total
variance. We find that the first factor explained only 26%
of the variance, which indicates that no single factor
could interpret most of the variance; therefore, the ho-
mology error of the research is not severe.
In addition, this study uses internal consistency
method to test Cronbach's α reliability. The reliabilities
of all variables are, inter-firm relationship (α = 0.6), in-
terperson relationship (α = 0.5), bank financing effi-
ciency (α = 0.7). Therefore, the variables in this study
have good reliability.
Table 1. Distribution of respondents.
N %
Sales revenues (in million RMB)
Less than 1 3 1.5
1-5 6 3.1
5-10 12 6.2
10-30 38 19.6
30-100 83 42.8
Above 100 52 26.8
Total 211 100
Total 211 100
Table 2. Correlation matrix and summary statist.
Variables 1 2 3
1. Inter- person relationship 1
2. Inter-firm relationship 0.184* 1
3. Bank financing 0. 173* 0.228**1
Mean 3.798 3.207 2.946
S.D. .5570 .4831 .7885
∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001 (two-tailed test)
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