2015 International Conference on Management Science & Engineering (22th)
October 19-22, 2015
Dubai, United Arab Emirates
“How Does Interdependence Impact on Buyer–Supplier Relationship
Performance?”-A Loose-Coupling View
KANG Hui-wen，CHANG Yu
School of Management, Northwestern Polytechnical University, Xi’an 710129, P.R.China
Abstract: This study presents an analysis exploring
how two types of interdependence (benefit based, cost
based) influence dyadic relationship performance in the
buyer–supplier context. Underpinned by loose coupling
theory, we build a mediating framework in which we
propose that a high level of interdependence drives
buyer–supplier relationship performance through
bolstered coupling links in mutual knowledge sharing,
continuous commitment, and relationship investment.
Our survey of 152 paired manufacturers (suppliers) and
distributors (buyers) in China generally supports this
argument, leading to a conclusion that interdependence is
not a direct determinant of buyer–supplier performance
but a critical conduit that nourishes mid-range coupling
behaviors, which in turn promotes a successful
relationship. Based on findings from this study, firms are
encouraged to endorse two kinds of interdependence in
managing supply chain relationships.
Keywords:
buyer-supplier
relationships,
interdependence, loose coupling theory, relationship
performance
1 Introduction
Interdependence is generally considered to be
important concept to understand buyer–supplier
relationships[1][2]. Following Emerson’s (1962) [3]
power-dependence
framework,
who
originally
researched on dependence, more and more researchers
pay close attention to dependence, and convert the focus
to the dependence on each other, that is
interdependence[4][5]. Interdependence is one of the
necessary conditions to build and develop a supply chain
relationship [6], because most organizations are not
self-sufficient, they always depend on their trading
partners for resources (eg: capital, human resources and
material) to achieve their goals. For example, in 2004,
two Chinese enterprises – Gome(Retailer) and Gree (the
air conditioner manufacturer) canceled their cooperation
relationship. When Gome’s made summer promotion
Supported by the Ministry of Education, Humanities and Social
Science fund(12YJA630008), Shaanxi Academy of Social
Sciences Fund (13Q108) and the Graduate Starting Seed fund
of Northwestern Polytechnical University (Z2015167)
978-1-4673-6513-0/15/$31.00 ©2015 IEEE
without Gree’s permission, they decided to withdraw all
of its products. Both two parties did not cooperate and
depend on each other. The ultimate result of lack of
interdependence was that Gree had to build its own retail
store to make up the loss in market share due to the
ended relationship with Gome that Gree couldn’t rely on
the retailer’s resource.
The above clearly shows the important role of
interdependence
in
managing
buyer–supplier
relationships. However, it seems that it is still often an
overlooked factor in conceptual and empirical studies [2].
Scholars have already begun to explore the relationship
between interdependence and relationship performance.
However, they focused on the structure of
interdependence. For example, Gundlach and
Cadotte(1994)[4] verify that total interdependence and
asymmetry independence respectively act on relational
behavior; QU Hong-min(2007)[7] testify the relationship
between interdependence structure and relationship
performance, moderated by environment uncertainty;
Ren Xingyao(2009)[8] empirically test and identify how
interdependence asymmetry in channel relationships
affects their relational performance. There are few
scholars researching on interdependence itself. Li guihua
(2014)[9] testified the two kinds of interdependence
(benefit based, cost based) directed influence the
relationship performance in supply chain. However, the
direct influence neglects the behavior mechanism.
In an effort to fill the gaps in interdependence
research in supply chain relationships, this study seeks to
explore the influence of different kinds of
interdependences on buyer–supplier relationship
performance. Borrowing loose coupling theory as the
theoretical lens [10], we propose that interdependence
promote their mutual coupling behaviors and, in turn,
lead to improved relationship performance. Loose
coupling theory, due to its simultaneous consideration of
indeterminacy (looseness) and determinacy (coupling) in
a relationship [11], is considered to be appropriate when
being applied to buyer–supplier relationships because the
buyer and the supplier are both separate (looseness) and
dependent (coupling) in supply chains[10].
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2 Theoretical development and hypotheses
2.1 Interdependence in buyer-supplier chains
According to resource dependence theory[12], very
few organizations can be internally self-sufficient which
causes interdependence. Interdependence is one of the
fundamental factors in buyer-supplier relationships [13].
Interdependence in supply chains can be defined as the
firms’ need to maintain its business relationships with
supply chain partners to achieve their goals [14]. Emerson
(1962) [3] suggested that high interdependence can
promote cohesion of a relationship. Over the last few
decades, the theoretical development of the
interdependence concept in buyer-supplier relationship
has come to include two dimensions –benefit based
dependence, cost based dependence [9][15]. Benefit-based
dependence represents the positive motivation, which
means the relationship provides them irreplaceable
benefits, while cost-based dependence represents the
negative motivation, rooted in the other latent costs that
erode one’s ability to replace the current partner. We
adopt this two dimensions measurement model, benefit
based interdependence and cost based interdependence,
to explore buyer-supplier relationship.
2.2 Loose coupling theory in buyer-supplier chains
Loose coupling is one conceptual tool that
emphasizes relational patterns, which captures some
important and underexplored features of interdependence
in organizations [10]. This paper borrows loose coupling
theory as the theoretical lens for explaining how
interdependence matter in buyer–supplier relationships.
Applying loose coupling logic to supply chains, we
preconceive a supply chain as a loosely coupled system
in which partners are independent, yet they share
resources mutually and work together to facilitate supply
chain functions [16]. The buyer and the supplier maintain
their individual roles while collaborating with each other.
Therefore, the buyer–supplier relationship is loose and,
simultaneously, coupled [16].
On the basis of Beekun and Glick (2001)[10],
integration enables the elements in supply chains to
function together, which refers to the coordination of
efforts between two parties in order to accomplish the
supply chain goals. Following Orton and Weick’s
(1990)[17] suggestion of sharing, focused attention, and
integration, Yi Liu(2012) [16] proposed that mutual
knowledge-sharing (i.e., sharing), mutual continuous
commitment (i.e., focused attention), and mutual
relationship
investment
(i.e.
integration)
are
buyer–supplier coupling behaviors to accomplish the
supply chain tasks. The three coupling behaviors exactly
represent the interdependence between buyer and
supplier. Mutual knowledge-sharing means that two
firms simultaneously and equally exchange relevant
knowledge and information through dynamic processes
[18][19]
. Mutual continuous commitment denotes that both
parties actively maintain and strengthen the exchange
relationship[20]. Mutual relationship investment indicates
that both parties make idiosyncratic investments in the
relationship, which creates a lock-in situation that two
parties are motivated to maintain the relationship[20]. This
paper extends the research of loose coupling theory, by
linking the coupling behaviors to dependence, examining
how each type of interdependence helps achieve supply
chain relationship performance by these three behaviors.
2.3 The link of coupling behaviors: between
interdependence and relationship performance
Interdependence
Mutual
Coupling
Behavior
Benefit
Based
Knowledge
Sharing
Buyer-supplier
Relationship
Performance
Cost
based
Continuous
commitment
Relationship
Performance
Relationship
investment
Coupling enhancement
Loose coupling theory
Fig.1 Depicts the theoretical model
which is elucidated in added detail below
In conclusion, loose coupling theory establishes a
framework to explore the relationship between
interdependence and relationship performance, through
buyer–supplier coupling behaviors in supply chains.
Interdependence provides the most fundamental
motivation for enterprise [21], to break through simple
trading relationship and devote to the development of
long-term cooperation for further couple the relationship.
In distribution channels or supply chains, when two
parties perform in exchange transaction, the concerted
practices are coupling links connecting them
together[16,19,22].
Thus, we dispute that interdependence drive
buyer–supplier relationship performance, because a high
level of interdependence can (1) improve the frequency
to share knowledge and information [9]; (2) stimulate
continuous trading and commitment [15]; (3) increase the
specific relationship asset investment [23]. For benefit
based interdependence, Scheer[15]proposed that this
interdependence deduce from the irreplaceable benefits
that the members can bring. Benefit based
interdependence induce that both parties’ frequent
information interaction. Such a two-way knowledge
sharing benefits both firms. As a result, the members see
benefits in maintaining the relationship, thus, they make
commitment, continuous trading to remain existing
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relationship [9] and actively seek further relationship
coupling [16]. The increasing of benefit based
interdependence reveals that the members prefer to gain
the benefit by remaining the relationship. Thus, the
relationship loyalty will accordingly increase [23]. As well,
a high level of interdependence also makes the parties
feel confident about further commitment to and
investment in the relationship. In contrast, a low or
asymmetrical
dependence
may
cause
severe
consequences, such as power inequity or opportunism
behavior, as the Gome&Gree case in China. Thus, we
propose:
H1. Benefit based interdependence is positively
related to buyer–supplier coupling behaviors.
Cost based interdependence means when the firms
in a long-term stable relationship or at economies of
scale, they will enjoy a lower procurement/market costs
or through joint action to reduce the potential cost to
cancel the double marginalized [24]. Interdependence is a
particular important factor in long-term relationships.
When firms realize the potential cost gradually
increasing, in the sake of avoiding more cost, they will
take some actions to maintain the relationship [9], such as
a compromise on price with information disclosure, a
commitment for more purchase/sale [23]. Commitment
means a desire for long-term and stable relationship. The
investment on the special assets contributes a lot to the
maintenance of the cost based interdependence
relationship because it not only an effective mechanism
of incentives for mutual guarantee, but also a restriction
of conversion. Therefore, when firms make commitment,
they will invest more special asset to show their
determination. Thus, we propose:
H2. Cost based interdependence is positively related
to buyer–supplier coupling behaviors.
The ultimate goal of the buyer and the supplier in
their relationship is to benefit from the relationship [20][16],
that means both parties could achieve better performance.
A relationship perspective can bring an added dimension
for performance, especially to the close, mutual
relationships[25]. Relationship performance provides a
wider view that measures the performance of a variety of
relationship activities for both parties. From
buyer–supplier perspective, the relationship performance
should focus both magnitude and symmetry[26]. As with
the performance within prior organization research, the
relationship performance includes financial and
nonfinancial dimensions. [27]. We assume that
benefit-based
interdependence
and
cost-based
interdependence between the buyer and supplier help two
firms form into an integrated coupling system, as they
carry out supply chain activities for the purpose of
mutual performance gains[10].
In a buyer–supplier relationship, mutual knowledge
sharing, continuous commitment, and relationship
investments signify that both parties want to cooperate
and couple with each other [16]. As for the three aspects
of couple behaviors, we analyze their relationship with
relationship performance as follows. Mutual knowledge
sharing promotes the interbehavior to make the
transaction more transparent, reduce the information
asymmetry and avoid misunderstanding. More
specifically, in buyer-supplier relationship, knowledge
sharing help them achieve a better understanding of
products, processes, competition and markets. Thus,
improve their problem-solving capabilities in
responding[19][28]; effectively avoid the opportunism
behavior and conflict; drives better and symmetric
relationship performance for the dyad [26].As for supply
chains, commitment means a long-term relationship
orientation that both parties would rather sacrifice or
give up short-term relationship to achieve long-term
interests of both parties[23]. Experience and research
suggests that continuous commitment help firms work
together to: (1) achieve their individual as well as joint
goals [16][29]; and (2) better meet the needs of customers,
thus enhancing mutual profitability [29]. In contrast, when
firms are unwilling to commit to long-term relationships
and to make investments to improve partner’s
performance, they may be unwilling to commit to
resource investments that are relationship specific. In
supply chains, the members see relationship specific
investments as vulnerable to opportunism when resource
commitments are not forthcoming from the other firms.
Further, the mutual relationship investment can not only
increases the importance of the relationship to each party,
but also improve relational stability and the effectiveness
of joint activities[16][30], resulting in better performance
for both parties[20]. Thus, we posit:
H3. Buyer–supplier coupling behaviors are
positively related to buyer–supplier relationship
performance.
3 Measures and results
3.1 Data
The research model proposed earlier is tested by
matched manufacturer-channel distributor data, in
organization level, gathered from the home appliance
industry
in
China,
specifically
in
Shaanxi
Province(Western
China),
Guangdong
province
(Southern China), Shanghai(Eastern China) and Beijing
(Northern China), representing the different regions of
China. Because the home appliance industry is an ideal
target for examining interdependence in buyer–supplier
relationship. As mentioned earlier, Gree is one of the air
conditioner manufacturers, while Gome is one of the
distributors. With the development of economy, the
competition within the Chinese home appliance industry
has heightened and the relationships between
manufacturers and distributors are getting tenser then
before. In general, the tense buyer–supplier relationships
are due to interdependence issues as illustrated in the
Gree& Gome case.
Then we designed matched questionnaires for
suppliers and buyers, respectively. In the process of
collecting dyadic data, we first phoned the informants
(marketing managers or directors of the about 800
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selected companies), and invite them to help us complete
the survey. Then we mailed them with our questionnaires
to 496 suppliers, who indicated accepting the invitation,
and also we asked them to recognize one of their major
distributors and to answer the questions related to their
relationship with this distributor. After reminders by
phone calls, visits, emails, we received 187 completed
questionnaires, with a response rate at 37.7%. And then,
we sent the matched questionnaires (second set) to the
distributors recognized by the participating suppliers. We
made greater efforts at this stage of data collection to
ensure our matched sample size. In addition to collecting
the survey via regular mail and phone, we deploy student
groups in person to collect data to the four cities or
provinces. The groups successfully collected 159
questionnaires from 187 distributors, 152 completed,
which represented an 81.2% response rate. Table 1
shows the descriptive statistics of suppliers and buyers in
our sample.
Tab.1 Profile of companies
Characteristics of Companies and Buyer
Respondents
1. Company age in years
10.52
Supplier
8.61
2. Relationship duration in years
6.27
6.27
3 .Location

(1)Northern China

(2)Southern China

(3)Western China

(4)Eastern China
%
23.35
21.72
28.30
26.63
%
21.73
29.70
26.55
22. 02
4.sales of company(in millions RMB)

(1)≤10

(2)10~50

(3)50~200

(4)More than 200

(5)Unreported
%
30.07
26.65
20.35
17.61
5.32
%
24.70
22.11
31.01
17.46
4.72
3.2 Variables and operationalization
In order to ensure the validity and reliability of
measurement tools, we use existing literature as far as
possible and modify the statement according to the
purpose of this paper. Table2 shows the items used to
measure each variable in this study and measurement
results. Each item’s Cronbach’s Alpha is greater than
0.70 indicating the measurement scales have good
reliability. And we conducted confirmatory factor
analysis (CFA) using AMOS 17.0, the fit indexes show a
good fit for both the buyer data(χ2= 573.34, df =315,
RMSEA =0 .04＜0.06; CFI =0.90＞0.90; TCI =0.92＞
0.90) and for the supplier data(χ2= 627.56, df =315,
RMSEA =0 .05＜0.06; CFI =0.91＞0.90; TCI =0.92＞
0.90). Then, we check the convergent validity of
measurement scales, as shown in table, factor loadings of
all the items are greater than 0.7. We also test
discriminant validity among the constructs, average
variance extracted (AVE) ( ＞ 0.50)of each construct
exceeds the squared correlation( Fornell and
Larcker ,1981). Moreover, we add two control variables
that may affect relationship performance into the tests,
firm size and relationship duration. Different firm size
(measured by sales revenue) may lead to imbalance
bargaining power, which could influence the distribution
of joint incomes (Subraman, 2003). Relationship
Duration, meant the year of a buyer–supplier relationship,
could impact relationship performance though longer
established relationships often lead to better tacit
understanding (Brown et al., 1995).
To operationalize the measures of dyads, we use the
measures propose by Straub et al. (2004) and Klein et al.
(2007). The approach can ensure simultaneous
estimating both magnitude and symmetry within the
dyad (Klein et al., 2007). We follow the procedure to do
our examination:(1) C1,C2 represent the magnitude for
the buyer and the supplier respectably, a standardized
value(between 0 and 1) of the scores for each items of
buyer data; (2) CD= (C1 + C2)/2, represents the degree
(magnitude) of the dyad data; (3) CS= C1/C2 or C2/C1
(divide the smaller one by the bigger one), which
represents the symmetric value of the construct; (4)
CDS=(CD+CS)/2, represents the degree-symmetric value
for the construct across the dyad. Then we operationalize
the degree-symmetric values for the constructs in the
proposed model.
Table 3 presents the means, standard deviations, and
zero order Pearson correlations for all of
degree-symmetric variables. And we check the
convergent validity using the degree-symmetric variables.
The fit indexes show a good fit for dyad data (χ2= 670.25,
df =315, RMSEA =0 .03＜0.06; CFI =0.90＞0.90; TCI
=0.93＞0.90).
3.3 Tests of hypotheses
We use multiple regression analysis to test our
hypotheses. The results of the analysis is shown in table
4. The mediation effect, according to the Baron and
Kenny's (1986), must meet the following conditions：
（1）
independent variable has significant influence on the
dependent variables ；（ 2 ） independent variables has
significantly influence on mediation variables；（3）
mediation variables have significant influence on the
dependent variables；
（4）the influence of the independent
variables on dependent variables disappear(complete
mediating effect) or less (partial mediation effect) when
the three kind variables all in the regression equation. As
shown in table 4，the interaction between benefit-based
interdependence with knowledge sharing (β = 0.25, p＜
0.01 ， M2), with relationship investment (β = 0.13,
p<0.05，M4), as well as the continuous commitment (β =
0.19, p＜0.01，M6) were positively significant. Thus, the
H1 is verified. The interaction between cost-based
interdependence and knowledge sharing(β = 0.19,
p<0.01. M2), with relationship investment (β = 0.40,
p<0.05. M4) as well as continuous commitment (β = 0.22,
p<0.01. M6) were positively significant. Thus, H2 is
verified. When we add the mediated variables
(knowledge sharing, relationship investment and
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Tab.2 Scale tems of research constructs
Factor
Scale
loadings
Items
(Reference)
B
S
We gain from doing business that couldn’t be
0.78 0.80
Benefit-based
fully duplicated with the next best alternative.
interdependence
If stopped sourcing/selling, we would be less
0.78 0.75
[Lisa
K.
attractive to our customers.
Scheer ][15]
The alternative would not be as effective
0.85 0.85
Costly to locate and implement a replacement if
Cost-based
0.78 0.77
interdependence ended the relationship.
[Lisa
K. Incur significant replacement costs if replaced.
0.79 0.81
Scheer ] [15]
Costly for us to end the relationship.
0.89 0.90
Knowledge on the product.
0.77 0.78
Knowledge
Knowledge about the market.
0.84 0.86
Sharing
Knowledge/skills on marketing and logistics.
0.89 0.87
[Kotabe] [31]
Knowledge on competition/threats.
0.91 0.92
If switch, we would lose the investment.
0.72 0.76
Relationship
Resources tailored to the relationship
0.79 0.81
Investment
0.87 0.87
[Anderson][ 32] We have made substantial investment.
We have invested its reputation/ networks.
0.76 0.78
Want to develop the relationship further.
0.77 0.76
Continuous
Plan to maintain the relationship for years.
0.89 0.86
Commitment
[Kim] [ 33]
We want to renew and extend our relationship.
0.74 0.74
Provided us with a dominant market position.
0.76 0.78
Relationship
Provided us with very attractive financial gains.
0.82 0.83
Performance
[Geyskens]
Provided us with increased customer traffic.
0.78 0.79
[ 34]
Provided us with improved process efficiency
0.79 0.77
Note: *B represents: buyer, S represents: supplier.
Cranach’s α
AVE
B
S
B
S
0.73
0.75
0.65
0.64
0.90
0.93
0.68
0.68
0.85
0.79
0.725
0.737
0.77
0.80
0.62
0.64
0.93
0.90
0.65
0.62
0.85
0.83
0.62
0.63
Tab.3 Means, standard deviations, and correlations
Variables
CDS Mean SD
1
2
3
4
5
Relationship Durationa
6.27
2.45
1.00
Firm Size
1.34
0.97 -0.10 1.00
Benefit-based Interdependence 0.79
0.07
0.09
-0.01
1.00
Cost-based Interdependence
0.82
0.10
0.06
-0.13* 0.17**
1.00
Knowledge Sharing
0.76
0.08
0.11
-0.04 0.45*** 0.39***
1.00
Relationship Investment
0.83
0.12 0.19** -0.03* 0.24*** 0.34*** 0.25***
Continuous Commitment
0.88
0.10 0.13** -0.02 0.37*** 0.44*** 0.32**
Relationship Performance
0.80
0.09 0.15*
-0.07 0.28*** 0.34*** 0.31***
Note: n=152； * p < 0.1, ** p < 0.05, *** p < .01
6
7
8
1.00
0.41***
0.38***
1.00
0.54***
1.00
Tab.4 Results of hypotheses tests
Knowledge Sharing Relationship Investment Continuous Commitment Relationship Performance
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
Control variables
Relationship Duration
0.07
0.08
Firm Size
-0.05**
-0.05
independent variable
Benefit-based Interdependence
0.25***
Cost-based Interdependence
0.19***
mediated variable
Knowledge Sharing
Relationship Investment
Continuous Commitment
R2
0.03
0.11
△R2
0.03
0.08
2.80
7.29***
F值
△F
2.80
26.12***
Note: n=152； * p < 0.1, ** p < 0.05, *** p < .01
0.08*
-0.02
0.09*
-0.04
0.06
-0.01**
0.13**
0.40**
0.11
0.00
3.19*
3.19*
0.14
0.03
7.01***
10.72***
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0.07
0.00
0.19***
0.22***
0.04
0.04
2.77**
2.77**
0.08
0.04
5.01***
13.49***
0.07** 0.07** 0.06* 0.08*
-0.05** -0.02** -0.04 -0.01
0.18**
0.20***
0.05
-0.23
0.16*** 0.19***
0.13** 0.17**
0.39*** 0.36***
0.19 0.08 0.10 0.20
0.15 0.00 0.02 0.10
3.33*** 4.30*** 4.60*** 9.16***
3.33*** 0.78* 5.96** 37.11***
continuous commitment) into the regression equation,
the influence of benefit-based(β=0.05. M10) and
to
cost-based interdependence (β=-0.23. M10)
relationship performance is not significant. Moreover,
the influence of coupling behaviors (knowledge sharing,
relationship investment and continuous commitment) is
significant. Thus, coupling behaviors play a complete
mediating role between interdependence and relationship
performance, which confirms H3 is verified.
4 Discussions and conclusions
This study explores how benefit-based and
cost-based interdependence drive buyer–supplier
relationship performance through coupling behaviors.
Through a research of 152 supplier–buyer dyads, we find
that a higher level of interdependence between two
parties is positively related to higher levels of coupling
behaviors through supply chain activities. In turn, a
higher level of coupling behavior contributes to a higher
relationship performance. The findings of this paper not
only provide new view for the interdependence and
supply chain management literature, but also have
practical implications in helping managers know the
function of interdependence between partnering firms
within the supply chain and to understand the mechanism
which interdependence influence buyer–supplier
relationship performance.
First, this research establishes a bridge from supply
chain management literature to relationship performance
by bringing in loose coupling theory, illuminating the
importance of interdependence in supply chains, which is
also a response to Beekun and Glick’s (2001)[10] request
for broadening researchers’ understanding of loose
coupling theory on inter-organizational linkages. By
viewing supply chains as loosely coupled systems,
applying the loose coupling theory could explain how
firms in supply chains react to the looseness of the
exchange relationship, and how they couple to gain more
from the relationship. Second, this study contributes to
buyer–supplier relationships research by using dyad as
the research unit and studying how interdependence
leads to relationship performance. Using the
degree-symmetry approach, we assess both the
magnitude of interdependence and symmetric degree.
Our results reveal that a high level of interdependence
drives relationship performance of the dyad. Moreover,
by viewing interdependence as immediate factor of
buyer–supplier coupling behaviors, we examine the
mediating roles of knowledge sharing, continuous
commitment and relationship investment in driving
relationship performance. Our research shows that three
coupling behaviors are full mediators between
interdependence and relationship performance. Thus, this
research clearly explains how interdependence drives
buyer–supplier relationship performance through the
coupling mechanism.
Based on findings from this study, firms are
encouraged to endorse two kinds of interdependence in
managing supply chain relationships to acquire a high
level of relationship. Our research reveals that only when
both parties simultaneously interdependence can a
relationship be profitable and stable. Moreover, the
mediate mechanism-loose coupling behaviors cannot be
neglect. Our research provides managers with clear
evidence that after mutual interdependence are achieved,
managers need to focus on identifying mutually
knowledge sharing, continuous commitment and
relationship investment that drive dyadic performance
and on motivating the engagement of both parties in the
behaviors.
Though we have thoroughly investigated the
consequences of interdependence in buyer–supplier
relationships, we have not taken some moderate factor
into the model. Future studies, then, may examine how
the environment or other factors may change the chain
relationships.
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