International Food and Agribusiness Management Review
Vol 6 Iss 2 2003
The Impact of Downstream Network Subgroups on Collaboration and
Performance: A Survey of Buyer-Supplier Relationships in the Dutch
Flower Sector
Danny Pimentel Claro, L Geoffrey Hagelaar, Ron Kemp and S.W.F. (Onno) Omta
a All
of the authors are of the Department of Business Administration, Wageningen University, The
Netherlands
Abstract
In this paper, we aim to identify those network subgroups that enhance the
collaborative governance in a focal buyer-supplier relationship. We argue, that
partners in a focal buyer-supplier relationship can be seen as embedded in a
broader network of business relationships with network subgroups, (e.g. other
buyers, buyers customers), which pro-vide information that can support the
collaborative governance, assessed by flexibility, joint planning and joint problem
solving, by lowering the level of information asymmetry between the partners.
Empirical evidence was gathered through a mailed questionnaire returned by 175
Dutch suppliers of potted plants and flowers. Our results show the importance of
the information provided by the network subgroups to manage the focal buyersupplier relationships and ultimately the impact on performance. Interestingly,
although five network subgroups were mentioned in the questionnaire, suppliers
only obtained reliable information for their focal relationship from the downstream
subgroups of other buyers (i.e. merchant-distributors) and buyer’s customers (i.e.
supermarkets and flower shops). In order to avoid redundancy, managers in seeking
information in their business network should not consider the network as a whole,
but rather the downstream subgroups.
© 2003 International Food and Agribusiness Management Association (IAMA). All rights reserved.
1. Introduction
L
Corresponding author: Tel: +31 317 482410
Fax: +31 317 485454
E-mail address: danny.claro@wur.nl
© 2003 International Food and Agribusiness Management Association (IAMA). All rights reserved.
D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
In this article, we propose that considering network connections allows a more
refined understanding of the relational governance of a buyer-supplier relationship
in marketing channels. Previous studies have concentrated mainly on the
organizational factors related specifically to the dyadic relationship – e.g. on
transaction specific investments (Dyer and Singer, 1998), trust (Anderson and
Narus, 1990), commitment (Anderson and Weitz, 1989), opportunism (Stump and
Heide, 1996), and on the exchange of information and data interchange between the
partners (Morgan and Hunt, 1994, Kraut et al, 1999). Less attention has been
directed to the influence of broader business networks on these dyadic relationships.
These studies have focused on commitment (Blankenburg Holm, Eriksson and
Johanson, 1999), innovation (Hakanson, Havila and Pedersen, 1999) and
contractual design (Antia and Frasier, 2001). However, so far no study has
investigated whether the information provided by the network connections – other
firms within a business network which are somehow connected to the exchange
partners in a focal business relationship – would influence the extent of
collaboration between the partners in a focal business relationship. Drawing on the
work of Anderson, Hakanson and Johanson (1994) and Burt (1997), we argue, that
partners in a focal buyer-supplier relationship can be seen as embedded in a
broader network of business relationships with network subgroups, (e.g. other
buyers, buyers customers), which provide information that can support the
collaborative governance by lowering the level of information asymmetry between
the partners. For instance, if a supplier has difficulties to set up the proper sales
conditions or is concerned about the reputation of the counterpart, he can rely on
the diligent information flows in the business network to make its decision.
Certainly not all the network subgroups possess valuable information and firms are
typically embedded in multiple, often overlapping set of relationships, so for
managers seeking efficiency, it is central to maintain connections with those
network subgroups that offer valuable information with no or limited redundancy.
In this paper, we aim to determine the specific network subgroups, which provide
valuable information that supports a focal business relationship in terms of its
collaborative governance and ultimately its performance. In § 2 we discuss the
theoretical background of the study and present the hypotheses. In § 3 we explain
the research design and in § 4 the results are discussed. Finally, in § 5 the
conclusions, managerial implications, and limitations and suggestions for further
research are presented.
2. Theoretical Framework and Hypotheses
The research model presented in figure 1 is not a full representation of all the
factors influencing a business relationship, but rather a set of hypotheses deduced
from relevant characteristics of network subgroups and the business relationship.
We will elaborate on the background of the model, the selected variables and
hypotheses, below.
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
Figure 1. Research Model
Other Buyers
Network Subgroup
Buyer’s Customers
Network Subgroup
H1a
Joint
planning
H2
Other PP Suppliers
Network Subgroup
H1b
Flexibility of
Adjustments
H1c
Shared Problem
Solving
H3
Input Supplier
Network Subgroup
Cooperative Agents
Network Subgroup
H4
H5
Perceived
Satisfaction
Growth Rate
Performance
Collaboration
Network Connection
Granovetter (1985) argues that information from a broader business network is
valuable because it is relatively cheap, and creates consistency in the context
surrounding a focal relationship. These informational benefits may include
monitoring of actions of the counterpart by other connected firms e.g. as a safeguard
against opportunistic behavior (Burt, 1997; Williamson, 1985), to improve the
coordination of production processes (Hakansson and Snehota, 1995; Hakansson, et
al, 1999), logistics (Gadde and Snehota, 2000), and the setting of a sales strategy
(Stern et al, 1996). Considering that there are innumerable potential connections
with different organizations to be considered (Ritter, 2000), a selection of the
relevant network connection becomes vital. Following Burt’s (1980) suggestion to
find a proper degree of actor aggregation, we decided to use the concept of network
subgroups that refers to a number of organizations with the same function in the
market. The subgroups can be not only the four subgroups located upstream (e.g.
colleagues/competitors and input suppliers) and downstream the market (e.g. other
buyers and buyers’ customers), but also the subgroup of third parties (e.g. mediation
agents).
Collaboration is a departure from the anchor point of discreteness that underlies
spot market transactions to a relational exchange as the roles of supplier and buyer
are no longer narrowly defined in terms of the simple transfer of ownership of
products (Macneil, 1981). By focusing on relational exchange, collaboration entails
the activities that are undertaken jointly rather than unilaterally (Heide, 1994;
Zaheer and Venkatraman, 1995). Within the framework of relational governance we
propose the following variables to be central: joint planning, joint problem solving
and flexibility of adjustments.
Joint planning refers to the joint activities by which future contingencies, and
consequential duties and responsibilities in a relationship have been explicitly made
ex-ante (Heide and John, 1990 and Heide and John, 1992). This is an action that is
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
basically proactive in nature, which operates as aids or frames of reference rather
than strict specification of duties as in a contract. Plans represent frameworks
within which subsequent adaptations (e.g. joint problem solving) can and are
expected to take place (Macneil, 1981). The supplier with good connections to
downstream network subgroups is more likely to get information on new trends and
new product demands, which may imply changes of the production and
transportation processes, e.g. the joint planning of the focal business relationship.
Joint problem solving refers to joint activities to resolve disagreements, technical
failures and other unexpected situations (Lush and Brown, 1996; Heide and Miner,
1992). This is a reactive action in which firms are looking for mutually satisfactory
solutions (Calantone, Graham and Wimsatt, 1998). Even though a reactive action in
nature, firms often attempt to persuade each other to adopt particular solutions to
the disagreement situation. In collaboration, these persuasive attempts are more
constructive than coercive or dominative (Dwyer, Schurr and Oh, 1987). Joint
problem solving can be influenced by the information of the network subgroups.
Several problems in business relationships are related to the definition of sales
conditions (Stern et al, 1996), and the resolution linked to the problems is
dependent on the information (Burt, 2001). The information gathered in the
business network might support the negotiation on prices, quantities and quality of
products. The problems related to production and logistic processes might have been
faced by other network connections that can provide the partners with solutions to
solve the problems.
Flexibility of adjustments refers to the extent to which a partner shows a flexible
response to changing circumstances (Heide, 1994). Flexibility is an essential
relational norm (i.e. an expected pattern of behavior, see Macneil, 1978, p.854),
which establishes the ground rules for the initial and future exchanges (Heide and
John, 1992). Much of the motivation for exploring the network is centered at the
new logic of production that requires flexibility, as opposed to mass production
(Powell, 1990). Markets for standardized goods are saturated, while higher quality
and more specialized goods attract consumers. To meet the demands of this
changing market place, firms adopt new modes of organization that spread
production across diversified inter-organizational linkages of other buyers,
suppliers, brokers, and buyers’ customers. Flexibility is central in collaboration,
since no plan can be implemented in full, and changes in circumstances occur
(Macneil, 1981). Even the simple planning of delivery, quantities and qualities is
subject to change and without flexibility of the partners it is quite likely that the
relationship fails. Flexibility is necessary to cope with the changing circumstances
that any supplier faces considering the complexity and risky nature of its processes,
even more so in agriculture production, which is very dependent on such uncertain
factors as the weather conditions. As problems emerge, the required flexibility
fosters teamwork between the partners. We expect that the more a supplier receives
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
information from the network subgroups, the more flexible the parties of a buyersupplier relationship will be.
Anderson and Narus (1990) found that firms engage in intensive collaboration with
a mutual interest in finding ways to add value or saving costs and primarily to
serve consumer needs, which in turn provide competitive advantage. The reasoning
underlying the expected positive influence of the three dimensions of collaboration
on performance is based on the reduction of transaction costs and achievement of
mutual expectations. Therefore, the time and energy so often spent on trying to
plan and work out problems without consulting the buyer is gained. Reviewing the
above, we formulate the following hypotheses:
There is a positive influence of the information provided by the network subgroups on
relational governance in terms of joint planning (H1a), joint problem solving (H1b)
and flexibility of adjustments (H1c).
There is a positive influence of flexibility of adjustments on joint planning (H2) and
joint problem solving (H3).
There is a positive relationship of relational governance on perceived satisfaction
(H4) and growth rate(H5).
3. Research Design
A sample of suppliers of the Dutch potted plant and flower sector was used to test
the hypotheses. This sector is one of the booming agribusiness sectors in the
Netherlands, accounting for over 65 per cent of the total world potted plant and
flower trade (Elshof, 1998). A specific interface in the sector was selected, namely
the business relationships between suppliers and merchant-distributors. This was
chosen because of the significant trade volume that is sold in direct collaboration
between suppliers and buyers via fixed lines, as opposed to the traditional auction
clock transactions (i.e. resembles a pure spot market). The fixed lines currently
represent over 50 per cent of the total sales of potted plants and flowers, as opposed
to less than four percent about five years ago (Kalenzi, 2000). Our respondents
(owners or managers of supplier companies) were asked to focus on the most
important wholesaler (hereafter referred to as the selected buyer) in terms of sales
via fixed lines in the previous year. Data were collected through the use of a written
questionnaire. The study sample consisted of 571 suppliers of potted plants and
flowers. Our data collection effort yielded 202 responses, of which 27 were
incomplete questionnaires and non-eligible companies, a response rate of 31%.
Questions address the relationship between a supplier and its most important
merchant-distributor in terms of purchases in the previous year. According to the
extrapolation method (Armstrong and Overton, 1977), non-response bias did not
appear to be a serious problem in our study.
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
A panel with practitioners and business academics and a pre-test with five
suppliers were used to develop the questions. We measured performance via
perceived satisfaction and growth rate. Perceived satisfaction refers to the rating of
the respondent’s satisfaction with its selected buyer (Bensaou and Venkatraman,
1995; Zaheer et al, 1998). Following Mohr and Speckman (1994) we used sales
growth rate in the last three years as an objective measure for performance, while it
was not possible to get reliable information on more direct measures, such as
operating profit margin. Flexibility of adjustments is a set of items describing the
parties’ expected flexibility in response to changing circumstances (Heide, 1994).
Joint planning measures the extent to which future contingencies and
consequential duties and responsibilities in a relationship have been made explicitly
ex-ante (Heide and John, 1990; Heide and John, 1992). Joint problem solving refers
to the behavior to the relationships that captures the degree of joint solutions to
problems a supplier demonstrates toward the selected buyer (Heide and Miner,
1992; Lush and Brown, 1996). The measurement instrument of network connection
was developed on the basis of previous research (Anderson et al, 1994; Blankenburg
et al, 1999). The measurement in those previous researches intended to capture the
“general effect” of other relationships on the focal relationships. We then made two
major adjustments to this instrument. First, we decided to include a third party
(e.g. a mediator) as connection. Second, this measurement instrument captures the
impact of five different types of informational benefits provided by five different
connections that are called network subgroups. A network subgroup is a set of
organizations with the same function in the market as perceived by the respondent.
The subgroups are shown in fig. 2, which represent the ones located upstream
(input suppliers and other supplier of potted plant products) and downstream (other
buyers and buyers’ customers), and the third party (agents of the auction
cooperatives).
The network subgroup of input suppliers (IS) includes the suppliers of young plants
and seeds, firms that supply fertilizers, chemical products, pots, vases, wood and
other raw materials; that of other buyers (OB) includes wholesalers, flower
exporters, cash and carries and garden centers; that of other potted plant supplier
(OPP) includes the firms with similar products; that of the buyers’ customers (BC)
includes supermarkets, flower shops and wholesalers abroad. The network
subgroup of agents of the auction cooperative (AC) is composed of the agents of the
mediation department of the auction cooperatives in the Netherlands, who have
strong contacts with the suppliers and buyers in this study. The informational
benefits of each network subgroup refer to the support for setting prices, setting
quantities, coordination of production processes and logistic operations, and
foreseeing future actions of the focal buyer.
Figure 2: Network subgroups (downstream network subgroups in dark gray)
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
AC 1 AC 2 AC n
IS 1
BC 1
IS 2
Respondents
IS 3
Selected
Buyer
BC 2
BC 3
OB 1
IS n
BC n
OB 2
OPP 1
OPP n
OPP 2
OB 3
OB n
AC: Agents of the auction cooperative; IS: Input suppliers; OPP: Other potted plant suppliers; BC:
Buyers’ customers; OB: Other buyers.
In order to test unidimensionality of the measurement instrument, an examination
of the item inter-correlations was used to purify the reflective scales (i.e. flexibility
of adjustments and joint problem solving). Although correlations between several
network subgroups and the dimensions of collaboration are significantly positive, all
of the correlations are below .60 (Churchill, 1979) dismissing any serious problem of
multicollinearity between the independent variables. The hypotheses were tested
based on structural equation modeling with Lisrel 8.50 (Jöreskog and Sörbom,
1996). To test for discriminant validity of these constructs, we conducted a
confirmatory factor analysis model with the two constructs where one had its factor
correlation fixed to unity (Steenkamp and van Trijp, 1991). The unconstrained
model provided a significantly superior fit, suggesting adequate discriminant
validity between the constructs. The scale composite reliability values of the
reflective scales all exceed the recommended value .70, which reflects the good
quality of the measurement instruments.
4. Results
The significant paths are displayed in figure 3 (for the non-significant paths, see
appendix). The structural model was judged to provide an acceptable goodness of fit
indices as well as statistically not significant associated chi square value (χ2=
26.455, p=0.019, df=12). This judgment is based on meaningful interpretability of
the model in terms of content and theory, the adequate value of .929 for the normed
fitted index (NFI), and the absence of normalized residuals with absolute values
greater than 2.32. This judgment is supported further by a goodness of fit index
(GFI) value of .972 and a standardized root mean square residue (RMSR) value of
0.048. In order to provide greater confidence to the results provided in table 1, we
tested our model (a restricted theoretical model MT) against two alternative
unrestricted models (Anderson and Gerbing, 1988 and Steekamp and van Trijp,
1991). The relevant test statistics lead to a non-significant chi-square difference test
and an acceptance of our model.
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
The model in figure 3 shows the direct impact of network subgroups on relational
governance and the indirect impact of network subgroups on performance. In
reviewing the total pattern of our results, we note that they highlight the
importance of reliable information provided by the downstream network subgroups
of other buyers (i.e. merchant-distributors) and buyer’s customers (i.e.
supermarkets and flower shops). Furthermore, they show the importance of
flexibility to enhance performance in terms of sales growth and perceived
satisfaction. The downstream network subgroups capture the information provided
by other buyers and buyers’ customers that supports suppliers in defining price and
quantities of products, coordinating the logistic and production process, and to
control the actions of the wholesalers. By gathering such valuable information,
suppliers can avoid surprises and take prompt action in the relationship with
wholesalers, because the information originates from subgroups close to consumers.
The action of planning together with the wholesaler requires a certain share of
supplier’s internal information, which relies on the support of colleagues and even
competitors that might have experienced similar situations with the same
wholesaler. By analyzing the three dimensions of collaboration, we tested the
strength of the dimensions in capturing the collaborative efforts. The results show
us that the norm of flexibility exerts a central role for collaborative channels with
wholesalers.
Figure 3. Path analysis results (standardized estimates: γ and β) of the model of business network
connections, the three dimensions of collaboration and performance.
2*
*
Joint
planning
†
*
63
.1
7
Buyers’ Customers .12
Network Subgroup
1**
.37
3**
Other PP suppliers .18
Network Subgroup
Flexibility of
Adjustments
.579
**
.222
.160 †
**
Growth Rate
.3 8 0
Input Supplier
Network Subgroup
†
-.113
Cooperative Agents
Network Subgroup
Perceived
Satisfaction
**
Downstream
the market
.2 2
Other Buyers
Network Subgroup
Joint Problem
Solving
χ2= 26.455 (P = 0.0195) df=12; GFI=0.972; RMSR= 0.048; NFI=0.929; **p<0.01, *p<0.05, †p<0.10, (two-tailed test).
The output generated by Lisrel also provides the total (direct + indirect) effects of
network subgroups on the three dimensions of collaboration and the two measures
of performance. The total effect coefficients corresponding to figure 3 are reported in
table 1. The total effect coefficients are interpreted in the same way as those related
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
to the individual paths. The result reinforces the importance of the downstream
network subgroups for suppliers dealing with wholesaling channels. The
information provided by downstream network subgroups, other buyers and buyers’
customers, influence positively perceived satisfaction and sales growth rate, and all
three dimensions of collaboration. This indirect effect of downstream network
subgroups is primarily mediated by flexibility and further mediated by joint
planning and joint problem solving. By considering the level of significance, it
appears that the network subgroup of other buyers evokes a stronger influence on
performance when compared to the subgroup of buyer's customers. The model in fig.
3, which based on its fit indices, has a high ability to predict the actual data and
captures the impact of these two downstream network subgroups on collaboration
and performance.
Table 1: Path model results - Total effects of network subgroups
Joint
Planning
Joint
Problem Solving
Flexibility of
adjustments
Perceived
Satisfaction
Growth
Rate
Other buyers
network subgroup
.082*
(2.240)
.128**
(2.368)
.222*
(2.453)
.092*
(2.014)
.046†
(1.778)
Buyers’ customers
network subgroup
.061†
(1.809)
.094†
(1.874)
.163†
(1.915)
.081†
(1.872)
.037†
(1.648)
Input suppliers
network Subgroup
-.017
(.538)
-.027
(.540)
-.046
(.541)
-.028
(.669)
-.014
(.625)
Other PP suppliers
network subgroup
-.033
(1.026)
-.051
(1.037)
-.089
(1.044)
-.007
(.154)
-.012
(.460)
Cooperative agents
network subgroup
-.022
(.784)
-.035
(.789)
-.060
(.792)
-.060
(1.578)
-.022
(1.067)
Downstream subgroups
Other subgroups
**p<0.01, *p<0.05, †p<0.10, two-tailed test.
Note 1: Lisrel total effect coefficients and |t-test| within parentheses.
Note 2: Lisrel total effect coefficients range from -1 to 1 and provide an indication of the relative magnitude of the
effects of each exogenous construct on the other furthest endogenous constructs within the context of the model
tested.
5. Conclusions and managerial Implications
Consistent with network scholars, who suggest that connections with members of
the network provide reliable information to support a business relationship
(Anderson et al, 1994, Gulati, Nohria and Zaheer, 2000), we found interesting
relations between the downstream network subgroups, collaboration and
performance. The results support to a great extent the hypotheses derived from the
framework in figure 1. It generally suggests that the studies of buyer-supplier
relationship should consider the implications of individual network subgroups on
the various dimensions of collaboration and performance and moreover that, in
developing collaborative channels with wholesalers, the building and sustaining
connections with downstream networks is critical. This supports a process view of
the business network relationships consistent with Granovetter’s (1985) concept of
structural embeddedness. This implies that when firms are interacting they are
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D. Claro, et al. / The International Food and Agribusiness Management Review Vol 6 Iss 2 2003
engaged in network structuring at the same time as they are conditioned by the
network structure (Burt, 1980).
Two managerial implications of our study appear to be most critical. First,
managers may use our study and its empirical evidence as a check on the adequacy
of their existing business network in terms of the information provided by network
subgroups. Second, it is important for managers to have an accurate perception of
the value of the information of each individual network subgroup. Without this, any
evaluation of the costs and benefits of alternative governance responses based on
market forces (e.g. market-based governance) and relational norms (e.g. relational
governance) would be vague.
Acknowledgements
Our special thanks go to the helpful assistance of A. van der Heiden of the Dutch
auction cooperative. The authors are grateful for the research grant provided by
CAPES (Project BEX 1257/98-6).
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Appendix 1:
Individual path results of the hypothesized relationship between network subgroups, collaboration and performance
Flexibility of Joint
Joint
Perceived
Growth
adjustments Planning
Problem Solving Satisfaction Rate
Downstream subgroups
Other buyers
network subgroup
.222**
(2.453)
.040
(.490)
.006
(.075)
Buyers’ customers
network subgroup
.163*
(1.965)
.127†
(1.688)
.042
(.594)
Input suppliers
network Subgroup
-.046
(.541)
.114
(1.528)
-.036
(.509)
Other PP suppliers
network subgroup
- .089
(1.044)
.183**
(2.443)
.087
(1.231)
Cooperative agents
network subgroup
.061
(0.792)
-.059
(.874)
-.113†
(1.794)
.371**
(5.506)
.579**
(9.125)
Other subgroups
Collaboration
.222**
(2.491)
.160†
(1.688)
Joint Planning
.014
(0.192)
.007
(.878)
Joint problem
solving
.380**
(3.654)
.089
(.946)
Flexibility of
Adjustments
Χ2 = 26.455 (P = 0.0195) df=12; GFI=0.972;
RMSR= 0.048; NFI=0.929
†
**p<0.01, *p<0.05, p<0.10, two-tailed test.
Note: Standardized estimates (γ and β) and |t-test| within parentheses.
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