Inter-organizational relationships and factors influencing information sharing

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JJIM-1020; No. of Pages 11

International Journal of Information Management xxx (2010) xxx–xxx

Contents lists available at ScienceDirect

International Journal of Information Management
journal homepage: www.elsevier.com/locate/ijinfomgt

Inter-organizational relationships and information sharing in supply chains
Jao-Hong Cheng ∗
Department of Information Management, National Yunlin University of Science and Technology, Douliou, Taiwan

a r t i c l e i n f o a b s t r a c t

Article history: This paper presents a research model to examine factors influencing information sharing and implemen-
Received 12 February 2010 tation in inter-organizational relationships. The model comprises seven research hypotheses with six
Received in revised form constructs, including relational benefits, relational proclivity, connectedness, power symmetry, dysfunc-
28 September 2010
tional conflict and information sharing. The constructs are measured by well-supported measures in the
Accepted 28 September 2010
literature. The hypotheses are tested via an empirical study of supply chains. Data are collected from
Available online xxx
589 manufacturing firms that are among the top 1000 Taiwanese manufacturing firms of 2009 listed by
Business Weekly. The results of the empirical study suggest that the role played by relational benefits
Keywords:
Relational benefit
is critical in ensuring the information sharing as it reinforces the connectedness between supply chain
Relational proclivity members and mitigates the dysfunctional conflicts in the process. The findings of the study provide useful
Connectedness insights into how supply chain members should reinforce their collaborative behaviors and activities so
Power symmetry as to improve their relational benefits and connectedness and in turn enhance information sharing for
Dysfunctional conflicts the supply chain as a whole.
Information sharing © 2010 Elsevier Ltd. All rights reserved.

1. Introduction Ishman, & Sanders, 2007). By taking greater information available
and sharing it with partners (Ellinger, Taylor, & Daugherty, 1999;
Inter-organizational relationships are built, maintained and Pereira, 2009) in the supply chains, such as subcontractors or sup-
enhanced to achieve business goals that might be difficult to accom- pliers, a manufacturing firm can make better decisions on ordering,
plish by individual organizations alone. In a supply chain setting, capacity allocation and production/material planning so that the
inter-organizational relationships are usually reflected through supply chain dynamics can be optimized (Huang et al., 2003). Inter-
partnerships or buyer–seller relationships. A supplier partnership organizational information sharing within the supply chains has
in the supply chains implies the agreement between a manufac- thus become a common practice, because it enhances the compet-
turing firm and its suppliers or subcontractors. It includes sharing itive advantage of the supply chain as a whole.
essential information with respect to limitations relevant to time To achieve the advantages of information sharing, it is of
and distance, as well as sharing risks and benefits that come strategic importance for the manufacturing firms to understand
along with the relationship. The buyer–seller relationships, for its those factors pertaining to inter-organizational relationships that
part, reflect strategic relationships among independent firms (Tang, affect the information sharing behaviors of their partners. Exist-
Shee, & Tang, 2001). Both partners in a relationship tend to collab- ing research on this important issue has focused on modelling
orate together if they perceive cooperation with each other will all the factors under investigation as precursors or independent
bring benefits or value. For a supply chain as a whole to achieve its variables that directly affect the behaviors of information shar-
competitive advantage, collaborative behavior and activities need ing, as shown in Table 1. In particular, few studies have examined
to be promoted to build value-based relationships among members how factors related to benefits in inter-organizational relation-
(Wang & Wei, 2007; William & Diana, 2007). ships affect the information sharing through other factors such
Information sharing has increasingly become an important issue as relational proclivity, connectedness, power symmetry, and dys-
for the supply chains. Information sharing significantly affects in functional conflict. Little is known about the implications that the
reducing supply chain costs (Gavirneni, Kapuscinski, & Tayur, 1996; inter-relationship between inter-organizational relational benefits
Huang, Lau, & Mak, 2003; Swaminathan, Sadeh, & Smith, 1997; and dysfunctional conflict has for effective information sharing
Tan, 1999), and achieving competitive advantage (Drucker, 1992; in situations involving networks that transcend organizational
Li & Lin, 2006; Li, Ragu-Nathan, Ragu-Nathan, & Rao, 2006; Shin, boundaries. Information sharing is determined by the trade-offs
among factors including dependence, uncertainty, exchange effi-
ciency, and social satisfaction, among others (Dwyer, Schurr, & Oh,
∗ Corresponding author. Tel.: +886 935654171; fax: +886 55312077. 1987). It is generally believed that willingness to share is greater if
E-mail address: jhcheng@yuntech.edu.tw parties have a close relationship.

0268-4012/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ijinfomgt.2010.09.004

Please cite this article in press as: Cheng, J.-H. Inter-organizational relationships and information sharing in supply chains. International Journal
of Information Management (2010), doi:10.1016/j.ijinfomgt.2010.09.004

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2 J.-H. Cheng / International Journal of Information Management xxx (2010) xxx–xxx

Table 1
Previous research summarizing the antecedents to information sharing in supply chains.

Previous research Context Antecedents to information sharing in supply chains

Li and Lin (2006) Between supply chain partners Environmental uncertainty, and intra-organizational facilitators
Patnayakuni, Rai, and Seth (2006) Between supply chain partners Long-term orientation, asset specificity, and interaction routines
Shin et al. (2007) Between organizations Guanxi, Confucian dynamism, and collectivism

Relational governance is a major perspective for the main- 2. Relational governance and information sharing in
tenance of inter-organizational relationships in supply chains supply chains
(Benton & Maloni, 2005; Carr & Pearson, 1999; Liu, Luo, & Liu,
2009). Relational governance is embodied in both the structure To improve supply chain coordination and product quality, man-
and the process of inter-organizational relationships, especially the ufacturing firms often demand that their supply chain partners
exchanges between organizations (Zaheer & Venkatraman, 1995). such as subcontractors or suppliers implement common processes
Thus, value-based relationships become part of relational gover- which often require the sharing of information (Ellinger et al.,
nance, which involves the evaluation of the risk and benefits that a 1999; Pereira, 2009). With collaborations between partners enables
company incurs through the relational exchange. Resource-based better information sharing and as a result greater competitive
view (RBV) concentrates on the specific relational resources, which advantages for each one. A primary objective of information shar-
can be measured based on the benefits gained through relation- ing is to speed up information flow (Chow, Choy, & Lee, 2007; Xu,
ships, among other factors. From the political economy perspective, Dong, & Evers, 2001), improve the efficiency and effectiveness of
inter-organizational linkages facilitate exchanges and reduce con- the supply chains, and respond to the changing needs of customers
flicts in supply chains (Cannon & Perreault, 1999; Stem & Reve, more quickly among inter-organizational members (Li & Lin, 2006),
1980). Because partners that deliver superior benefits will be highly which is important in the maintenance of good relationships.
valued, firms will commit themselves to establishing, develop- Relational governance is a key determinant of competitive
ing, and maintaining relationships with such partners (Morgan & advantage, which concerns the maintenance of the relationship
Hunt, 1994). As such, both partners in a relationship begin to value of a company with its supply chain partners (Heide & John, 1992;
the relationships and will diminish the probability of relational Josi & Campbell, 2003; Wang & Wei, 2007). Relational governance
risk behaviors (such as power symmetry, dysfunctional conflicts). has been shown to solve exchange problems and enhance per-
Consequently, this study draws on the theories of relational view formance (Heide & John, 1988). Several prevailing theories have
(such as resource-based view and political economy perspective), recommended relational governance for managing supply chain
supplemented by the relational risk, to examine what value- relationships. Resource-based view and political economy perspec-
based relationships can improve information sharing in supply tive as theories of relational view emphasize the collaboration
chains. for generating value from resource-based and political economy
To address the important issue of information sharing improve- frameworks. The establishment of a high level of information
ment in the context of supply chains, a research model is sharing through close relationships among supply chain partners
developed in this study for the investigation of factors influenc- enhances the competitive advantage of the supply chain as a whole
ing inter-organizational information sharing. The study contributes (Holland, 1995).
to relevant literature in three major ways. First, this work Resource-based view is a major theoretical perspective for ana-
provides insights into how inter-organizational information shar- lyzing specific relational resources in supply chains (Chang & Shaw,
ing can be enhanced by the relational benefits of partnership 2009; Griffith, Myers, & Harvey, 2006; Marcus & Anderson, 2006;
in supply chains. Second, this investigation suggests that the Ranganathan, Dhaliwal, & Teo, 2004; Subramani, 2004). Relational
role played by relational benefits is critical in ensuring the resources are key determinants of competitive advantage because
information sharing as it reinforces the connectedness between they provide a firm with a unique resource barrier position in the
supply chain members and mitigates the dysfunctional conflicts supply chain (Chang & Shaw, 2009; Dyer & Singh, 1998; Griffith
in the process. Third, rather than focusing on the antecedents & Harvey, 2001; Griffith et al., 2006; Marcus & Anderson, 2006;
to information sharing, this research model reveals how infor- Ranganathan et al., 2004). Relational benefits as an important ele-
mation sharing is significantly affected by inter-organizational ment of relational resources are consistent with the value-based
relational benefits through other mediating variables, including perspective (Ulaga & Eggert’s, 2006). According to this perspective,
relational proclivity, connectedness, power symmetry, and dys- creating superior customer value is fundamental to a firm’s long-
functional conflict. The first two variables are in relation to the term survival and success in supply chains (Slater, 1997; Woodruff,
political economy perspective, and the last two are related to 1997). The critical role of relational benefits in interfirm collab-
the relational risk perspective. To verify this research model, orations is supported by Ulaga and Eggert’s (2006) findings that
an empirical study of Taiwan’s top 1000 manufacturing firms relational benefits take on more weight than relational costs in the
and their supply chain suppliers and subcontractors was con- formation of customer value in business markets. From the polit-
ducted. ical economy perspective, inter-organizational relationships are
In subsequent sections, we first give an overview of rela- influenced by their sociological elements (Li et al., 2006; Michael,
tional governance and information sharing in supply chains. Next 2000). Relational proclivity and connectedness are among the most
we discuss the factors affecting inter-organizational information key facets of the “relational” norms (Hartley & Benington, 2006;
sharing and present the research model with seven hypotheses. Johnson & Sohi, 2001).
Thereafter the survey instrument developed and data collected In addition to RBV and political economy perspective, the sup-
from Taiwan’s major manufacturing firms using structural equa- ply chain management literature has applied the relational risk
tion modeling are described. Finally, we discuss the results, their (Delerue, 2005; Ratnasingam, 2007) to inter-organizational rela-
practical implications and limitations, and suggestions for future tionships. The concept of relational risk includes the probability
research. and consequence that partners do not cooperate in a desired man-


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J.-H. Cheng / International Journal of Information Management xxx (2010) xxx–xxx 3

Relational +H3 Connectedness are greater than that of other companies. Research has found
Proclivity
+H1
that offering superior benefits to the customer play a critical role
+H5 in value-based business relationships (Ulaga & Eggert’s, 2006).
Relational Benefit -H4 Information
Sharing
In a supply chain, organizations tend to band together if they
perceive their cooperation will bring benefits that add value to
-H7
-H2 -H6 the inter-organizational relationships. In other words, Relational
Power Symmetry Dysfunctional
Conflict benefits indeed affect the customers’ willingness to build and main-
tain a long and positive relationship with the company (Gwinner,
Fig. 1. The research model. Gremler, & Bitner, 1998). Relational proclivity is thus a vital fac-
tor determining the commitment of customers or partners to their
relationship with the company. As such, it is hypothesized that:
ner (Das & Teng, 2001). They are derived from the failure to address
power related issues among partners (Ratnasingam, 2007). Rela- H1. Relational benefits are positively related to relational procliv-
tional risk includes parallel risks associated with the cooperation ity.
and risks associated with partner’s behavior (Delerue, 2005). In
this study, we use the widely recognized factors related to part- Power in an inter-organizational relationship implies the ability
ner’s relational risk behaviors in a supply chain, including power of a firm to compel compliance (Morgan & Hunt, 1994). In a supply
asymmetry and dysfunctional conflict. chain, power indicates a partner’s degree of dependence resulting
The value created by collaborative supply chains benefits all from relational benefits provided by the dominating company. This
parties (Horvath, 2001). With respect to inter-organizational infor- degree of dependence varies from one firm to the next according
mation sharing, cooperation has the potential to increase each to the benefits each firm is able to offer to the partner. The partner
party’s information base and consequently competitiveness, as will choose to cooperate with the firm that provides it with greater
information is a source of competitive advantage (Drucker, 1992; benefits. This relationship indicates that the partner depends on
Mentzer, Min, & Zacharia, 2000). Organizations tend to band the firm which possesses power. In line with organizational behav-
together if they perceive that cooperation with each other will ior literatures, there are not all relationships resulting in mutual
bring benefits to the inter-organizational relationships. As such, benefit (Hingley, 2005; Svensson, 2001). Research has found that
both partners in a relationship begin to value the relationships actor A’s power in the relationship with B is the inverse of B’s
and will not behave opportunistically because they do not want dependence on A (Dapiran & Hogarth-Scott, 2003; Emerson, 1962;
to jeopardize that relationship (William & Diana, 2007). While the Hingley, 2005; Rokkan & Haugland, 2002). Dependent relation-
existence of this issue is well-known, little work has focused on ships are characterized by an imbalance of power (Cook & Emerson,
how the issue may be examined and modeled. 1978). It is thus hypothesized that:
To address this issue in supply chains, this study examines how H2. Relational benefits are negatively related to power symmetry.
inter-organizational relational benefits through relational procliv-
ity, connectedness, power symmetry and dysfunctional conflict
3.2. Relational proclivity
affect information sharing in supply chains. Relational benefits,
relational proclivity, and connectedness are used to measure
Relational proclivity refers to the strength of the general ten-
benefits derived from relationships, predisposition to form rela-
dency held by a firm to seek out, engage in, and make close
tionships, and level of dependence of relationships, respectively.
partner-style inter-organizational relationships as opposed to con-
The constructs and hypotheses of the research model are discussed
ducting inter-organizational interaction at arm’s-length (Johnson
in the following section.
& Sohi, 2001). Relational proclivity plays a vital role when a com-
pany is building up a relationship with other companies. From an
3. The research model organizational point of view, relational proclivity refers to benefits
and advantages that accrue while companies are in an inter-
Fig. 1 shows the research model with the factors. It begins with organizational relationship. With relational proclivity, there will
inter-organizational relational benefits and then proceeds on to be no huge problem in sharing tasks (Larson, 1992) and reach-
the mediating variables which also affect information sharing. As ing consensus when partners are engaged in making decisions. In
already mentioned, these mediating variables are relational pro- addition to other advantages, the company often sees gains in pres-
clivity, connectedness, power symmetry and dysfunctional conflict. tige from association with certain partners in inter-organizational
Seven hypotheses were tested with respect to this model. Each relationships (Larson, 1991).
hypothesis is indicated by the letter H and a number. The arrows Customer relational proclivity plays a vital role when the cus-
indicate the hypothesized relationships, and the plus and minus tomer is building up the relationship with the company. It is a
signs indicate positive and negative relationships respectively. relatively stable and conscious tendency of the relationship a cus-
tomer is engaging with retailers of a particular product category
3.1. Relational benefit (Wulf, Odekerken-Schroder, & Lacobucci, 2001). These relationally
predisposed partners will be more inclined to commit manage-
Relational benefits may include dimensions pertaining to rial resources in terms of time and effort to inter-organizational
product profitability, customer satisfaction, and market share per- relationships (Johnson & Sohi, 2001). With relational proclivity,
formance (Morgan & Hunt, 1994). A company will take relational inter-organizational relationships that begin with a central or pri-
benefits into consideration when deciding to link with other com- mary exchange may often enlarge into diverse aspects, with an
panies. The relationship will be established only if it is expected to array of advantages and benefits (Larson, 1992). This process is
benefit the company. Relational benefits become a crucial factor in aided by frequent and extensive managerial interaction with inter-
determining the relationship commitment. As such, relational ben- organizational relationships partners at multiple levels in the firms
efits dominate when deciding which supplier to name first among (Johnson & Sohi, 2001). In an inter-organizational relationship,
a set of available suppliers (Ulaga & Eggert’s, 2006). strong relational proclivity indicates that a firm shall maintain
In service relationships, the customers’ loyalty toward a com- positive relationships with its partners. Therefore, firms that have
pany reflects that relational benefits provided by the company strong relational proclivity are prone toward build high levels of


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connectedness (Johnson & Sohi, 2001). It is therefore hypothesized asymmetric relationships are associated with less stability and
that: more conflict (Ganesan, 1994; Hingley, 2005; Rokkan & Haugland,
2002).
H3. Relational proclivity is positively related to connectedness.
The bilateral deterrence theory (Bacharach & Lawler, 1981;
Lawler, Ford, & Blegen, 1988) declares that higher degrees of aggres-
3.3. Connectedness
sion and conflict result if interdependence asymmetry increases
(Bacharach & Lawler, 1981; Cook & Emerson, 1978; Lawler et al.,
Connectedness indicates the dependence on each other for
1988; Molm, 1989; Rokkan & Haugland, 2002). As the structure of
assistance, information, commitments or in respect of other behav-
channel interdependence becomes more asymmetric, companies
iors that encourage coordination among individuals, departments,
with equal power are not going to have a strong motivation to avoid
or organizations (Hartley & Benington, 2006). Connectedness is
conflict (Kumar & Van Dissel, 1996). The bilateral deterrence theory
formed by the relationship between a firm and other firms. The
also states that there is a great possibility of conflict if the rela-
inter-organizational relationship can be adjusted according to the
tionship between a relatively powerful firm and its weaker partner
strength or extent of connectedness between the partners. There-
is asymmetric. Therefore, firms with greater interdependence and
fore, greater interdependence will cause a higher degree of shared
symmetry need not worry about dysfunctional conflict and the
understanding and lead to a more harmonious and market-oriented
damage it can do to their relationships. When the degree of interde-
relationship (Johnson & Sohi, 2001).
pendence increases, lesser conflict will occur. This is because firms
Great dependent can lead to higher levels of mutual under-
depend on each other. Each party holds enough power to harm the
standing and rapport between partners because it is their mutual
other party. As a result, there will be severe loss to both parties if
self-interest to collaborate (Anderson, Lodish, & Weitz, 1987; Kohli
dysfunctional conflict happens.
& Jaworski, 1990; Menon, Bharadwaj, & Howell, 1996; Narver &
The more equal the power in the relationship, i.e. the higher the
Slater, 1990). As such, greater dependence between parties of an
power symmetry, the stronger the degree of interdependence. In
inter-organizational relationship usually lowers dysfunctional con-
relationships characterized by power that is symmetrical, neither
flict (Anderson & Narus, 1990; Menon et al., 1996). Connectedness
partner in the relationship will insist on or rebuke ideas shared by
can also lower dysfunctional conflict (Barclay, 1991). It is thus
each other. The likelihood of dysfunctional conflict taking place,
hypothesized that:
however, is higher, when the power is asymmetric (Lin & Germain,
H4. Connectedness is negatively related to dysfunctional conflict. 1998). The weaker party will engage in some actions (i.e. dis-
tort or withhold information) to elevate the degree of symmetry
To improve inter-organizational coordination and product qual-
when the power is imbalanced (Morris & Cadogan, 2001). This
ity, manufacturing firms often require their supply chain partners
is also apt to occur when the powerful party refuses the adjust-
sharing valuable information (Bafoutsou & Mentzas, 2002; Li &
ment proposed by the weaker side. Accordingly, it is hypothesized
Lin, 2006; Pereira, 2009). The more and better the information
that:
shared with a firm, the greater the competitive advantage it
acquires. Thus, if high quality information sharing characterizes an H6. Power symmetry is negatively related to dysfunctional con-
inter-organizational relationship, the competitive advantage of the flict.
supply chain as a whole will be enhanced (Holland, 1995). Informa-
tion sharing processing theory provides yet another perspective.
When an inter-organizational relationship is thick, interaction 3.5. Dysfunctional conflict
and communication is frequent and multiple levels of management
are involved in the interaction between the partner firms (Johnson Conflict in inter-organizational relationships refers to the dis-
& Sohi, 2001). Strong healthy communication patterns certainly agreements that occur in the cooperation relationship or the
increase the probability that meaningful information sharing will incompatibility of activities, shared resources, and goals between
be conducted between the partners (Larson, 1991; Mohr & Sohi, partners (Anderson & Narus, 1990). Traditionally, all conflicts are
1995). Such communication patterns between the partners have seen as dysfunctional conflicts. Dysfunctional conflict constitute
been conceptualized as including productive content (Mohr, Fisher, unhealthy behaviors such as distorting information to harm other
& Nevin, 1996). When these communication patterns expand to decision makers, interacting with each other with hostility and
include multiple levels of managerial hierarchy as suggested in high distrust (Thomas, 1990; Zillmann, 1988), or forming barriers dur-
levels of connectedness, the likelihood of substantive information ing the process of decision-making (Ruekert & Walker, 1987).
sharing between the partners increases (Johnson & Sohi, 2001). For Dysfunctional conflict has an opportunistic side because many
these reasons, it is thus hypothesized that: members place an emphasis on needs when influencing others
(Barclay, 1991) and on information gatekeeping (Jaworski & Kohli,
H5. Connectedness is positively related to information sharing. 1993). Dysfunctional conflict and the typically unhealthy behav-
iors that precede and proceed from it lower cooperation and
3.4. Power symmetry decrease the quality of strategy planning and implementation that
require a coordinated effort to be successful (Ruekert & Walker,
Power is the ability to evoke a change in others’ behavior, includ- 1987).
ing the ability to cause others to do something they would not Relational conflict, especially dysfunctional conflict, has neg-
have done otherwise (Dapiran & Hogarth-Scott, 2003; Gaski, 1984; ative implications on team and organizational functioning since
Hingley, 2005; Rokkan & Haugland, 2002). In other words, hav- the practices of assessing new information provided (Pelled, 1996)
ing power over others is to have the ability to condition others and processing complex information (Panteli & Sockalingam, 2005;
(Thorelli, 1986). From partner’s perspective, power is indicative Staw, Sandelands, & Dutton, 1981) are inhibited. A dysfunc-
of its degree of dependence on (Dapiran & Hogarth-Scott, 2003). tional conflict negatively affects effective decision-making and the
In a dependent relationship, the power between parties of an processes that inform it, i.e. it is an impediment to effective inter-
inter-organizational relationship is imbalanced (Cook & Emerson, organizational information sharing. As such, it is hypothesized that:
1978). In inter-organizational relationships, there is an emphasis
on the necessity for symmetry and mutuality and that symmet- H7. Dysfunctional conflict is negatively related to information
ric dependence structures foster longer-term relationships, while sharing.


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Table 2
Constructs and measures of the research model.

Construct Source

Relational benefits
RB1 Averagely speaking, the expected product profits of Anderson and Narus (1990)
you and your partner in your cooperation is good.
RB2 Averagely speaking, the expected product
performance of you and your partner in your
cooperation is good.
RB3 Averagely speaking, the expected satisfaction of
you and your partner in your cooperation is good.
Power symmetry
PS1 You don’t respect your partner. Hunt and Nevin (1974), Brown, Lusch,
& Nicholson (1995) and Morris and
Cadogan (2001)
PS2 You don’t have the ability to withdraw yourself
from your partner.
PS3 You don’t have decision making power in the
cooperation relationship.
Relational proclivity
RP1 Closer partner-type relationships with your Johnson and Sohi (2001)
partner offer a major advantage in doing business.
RP2 Teaming up and working closely with your partner
allow you to be more effective.
RP3 It is appropriate to share proprietary information
with your partner if it is useful to do so.
Connectedness
CO1 When the need arises, you can talk to your partner Jaworski and Kohli (1993) and Rose
without formal channels. and Shoham (2004)
CO2 You and your partner are accessible with each
other.
CO3 There are alternative ways for communication.
Dysfunctional conflict
DC1 You will interfere with the decision making Menon et al. (1996) and Morris and
process in the cooperation. Cadogan (2001)
DC2 You will overstate your needs to try to influence
your partner.
DC3 You will overstate some information or facts to try
to influence your partner.
Information sharing
IS1 Our partners share proprietary information with Li and Lin (2006)
us.
IS2 We provide information to our partner that might
help our partner.
IS3 We provide information to our partner frequently
and informally, and not only according to the
specific agreement.

4. Research method its suppliers or subcontractors. Based on literature and recom-
mendations from practitioners, it was decided to choose function
To develop the survey instrument, a pool of items was identi- managers who are in the senior management team and are involved
fied from the literature in order to measure the constructs of the in maintaining and developing inter-organizational relationships
research model. Data from a survey sample were collected to assess with suppliers or subcontractors of the firm as respondents for
the instrument’s validity and reliability and to test the hypothe- the current study. A survey package comprising (1) a cover let-
sized relationships of the research model. ter explaining the research objectives, (2) the questionnaire, and
(3) a self-addressed stamped envelope was distributed to function
managers of each participating firm. The respondents were asked to
4.1. Measures complete the questionnaire and provide comments on the word-
ing, understandability and clarity of the items, as well as on the
All measures of the survey instrument were developed from the overall appearance and content of the instrument. The responses
literature. Where appropriate, the manner in which the items were suggested only minor cosmetic changes, and no statements had to
expressed was adjusted to the context of supply chains, as shown be removed. After the minor changes were made, and after a fur-
in Table 2. The items measured the subjects’ response on a seven- ther review by two other expert academics, the instrument was
point Likert scale ranging from ‘strongly disagree’ (1) to ‘strongly deemed ready to be sent to a large sample in order to gather data
agree’ (7). to test our research model. Table 2 shows the 18 items together
A pre-test was performed with four expert academics and five with the corresponding constructs that were measured.
Ph.D. students on a questionnaire consisting of 18 items of the
survey instrument to consider improvement in its content and
appearance. Thereafter, several large manufacturing firms were 4.2. Data collection procedure
contacted to assist with pilot-testing the instrument. This study
sought to choose respondents who were expected to have the Two rounds of surveying were conducted by distributing the
best knowledge about the operation and management of the inter- survey instrument in the form of a questionnaire to the function
organizational relationships between their manufacturing firm and managers of 1000 manufacturing firms in Taiwan. These firms are


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Table 3
Profiles of participating manufacturing firms.

Demographic profile Number of firms Percentage Chi-square df p value

Industry type
Food/beverage 37 5.2
Textiles/fiber 31 4.4
Printing and related support activities 8 1.1
Chemical/plastics 113 16.0
Non-metallic mineral products 17 2.4
Basic metal industries 66 9.4 10.022 10 0.415
Electrical machinery/machinery and equipment 92 13.0
Electronics/communication 16 2.3
Transport equipment 34 4.8
Electronic parts and components 274 38.8
Others 18 2.6
Total sales revenue (New Taiwan $)
Below $2 billion 87 12.3
$2.1 billion to below $3 billion 94 13.3
6.815 7 0.609
$50.1 billion and above 15 2.2
Years of establishment
Less than 5 years 5 0.6
6–10 years 68 9.5
11–15 years 99 14.1
16–20 years 84 12.0 7.101 6 0.492
21–25 years 120 17.0
26–30 years 90 12.8
Over 31 years 240 34.0
Position of respondent
Top managers 352 49.8
Function managers 237 33.6 4.128 2 0.625
Lower level managers 117 16.6

listed in the Business Weekly (Taiwan’s leading business magazine) 5. Data analysis and results findings
as the top 1000 manufacturing firms of 2009. The first round yielded
598 effective responses and the second round yielded an additional Structural equation modeling (SEM) with LISREL 8.52 (Joreskog
108 responses. This resulted in 706 effective responses and a total & Sorbom, 1993) was used to test and analyze the hypothesized
response rate of 70.6%. relationships of the research model. SEM aims to examine the
Additionally, the 589 respondents (83.4% of 706 effective inter-related relationships between a set of posited constructs
responses) were function managers or other managers in the senior simultaneously; construct is measured by one or more observed
management team such as general manager, vice president, or items (measures). SEM involves the analysis of two models: a
CEO. To check for the potential bias of a single informant, the con- measurement (or factor analysis) model and a structural model
sistency between the data collected from function managers and (Anderson & Gerbing, 1988). The measurement model specifies the
other senior mangers was verified. Consistent with past research relationships between the observed measures and their underly-
(Weil, 1992), interrater reliabilities (IRR) (James, Demaree, & Wolf, ing constructs – the constructs are allowed to inter-correlate. The
1984) were calculated to show the agreement level between func- structural model specifies the posited causal relationships between
tion managers and other senior mangers. The average estimates of the constructs.
IRR were 0.882 for relational benefit, 0.924 for relational proclivity,
0.813 for connectedness, 0.852 for power symmetry, 0.916 for dys- 5.1. Assessment of the measurement model
functional conflicts, and 0.931 for information sharing, respectively.
All estimates exceeded the recommended cut-off value of 0.7 (Eby With the measures and their underlying constructs shown
& Dobbins, 1997), indicating the response consistency between the in Table 2, the measurement model specified for the research
two groups. To ensure the result from strategy level managers, this model was assessed to ascertain the extent to which the observed
empirical model uses 589 function managers or other mangers in measures (surveyed items) were actually measuring their corre-
the senior management team as respondents. sponding construct. The 18 items of the survey instrument were
A chi-square analysis of the industry distribution of the respon- first analyzed to assess their dimensionality and measurement
dents showed no difference from the industry distribution of all the properties. All items loaded significantly and substantially on
firms used in the survey. The respondents were then further divided their underlying constructs, thus providing evidence of convergent
into two groups, including respondents and non-respondents. The validity. Using a confirmatory factor analysis, all items were found
comparison on industry type, total sales revenue, and years of to perform well and were thus retained in the model.
establishment of the two groups also showed no significant differ- The chi-square of the measurement model was significant
ences based on the independent sample chi-square test (p = 0.612, ( 2 = 76.21, df = 434, p < 0.001); with the value of 2 /df which was
0.532 and 0.734, respectively). This suggested a no non-response smaller than 2 indicated an ideal fit (Bentler, 1990). The large
bias in the returned questionnaires. Table 3 shows the demographic chi-square value was not surprising since the chi-square statis-
and characteristic profiles of participating firms. tic has been shown to be directly related to sample size (Joreskog


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Table 4
Assessment results of the measurement model.

Construct Items Standardised loading Standardised error t-Value SMC Mean S.D. CR AVE

RB1 0.768 0.149 8.121*** 0.579 5.22 0.918
Relational benefits RB2 0.916 0.138 3.848*** 0.835 5.46 0.913 0.931 0.819
RB3 0.771 0.159 8.085*** 0.586 5.59 0.911
PS1 0.947 0.103 2.791*** 0.889 4.65 0.956
Power symmetry PS2 0.771 0.295 6.323*** 0.443 4.86 0.981 0.910 0.772
PS3 0.781 0.221 8.332*** 0.421 4.97 0.994
RP1 0.927 0.104 3.912*** 0.839 4.22 1.128
Relational proclivity RP2 0.815 0.135 6.212*** 0.431 4.91 0.981 0.917 0.786
RP3 0.878 0.386 6.308*** 0.639 4.31 1.092
CO1 0.841 0.169 4.956*** 0.688 5.24 0.916
Connectedness CO2 0.781 0.074 5.213*** 0.676 5.51 0.915 0.932 0.821
CO4 0.738 0.161 8.877*** 0.389 5.52 0.910
DC1 0.872 0.126 6.219*** 0.658 4.08 1.069
Dysfunctional conflict DC2 0.739 0.162 7.862*** 0.512 4.71 0.944 0.919 0.793
DC3 0.728 0.191 7.881*** 0.513 4.62 0.871
IS1 0.937 0.228 3.219** 0.869 4.36 1.179
Information sharing IS2 0.926 0.261 3.315*** 0.839 4.28 1.132 0.914 0.780
IS2 0.915 0.237 3.401*** 0.826 4.37 1.115

** and *** denote significance at = 0.01 and = 0.001, respectively.

& Sorbom, 1993). To assess the overall model fit without being 5.4. Hypotheses testing
affected by sample size, alternative stand-alone fit indices less
sensitive to sample size were used. These indices included the In SEM analysis, the relationships among independent and
goodness of fit index (GFI), the adjusted goodness-of-fit index dependent variables are assessed simultaneously via covariance
(AGFI), the comparative fit index (CFI), the root mean square resid- analysis. Maximum Likelihood (ML) estimation is used to estimate
ual (RMSR), and the root mean square error of approximation model parameters with the covariance matrix as the inputted data.
(RMSEA) (Joreskog & Sorbom, 1993). For a good model fit, the GFI The ML estimation method has been described as being well suited
should be close to 0.90, AGFI more than 0.80, CFI more than 0.9, to theory testing and development (Anderson & Gerbing, 1988; Hair
and RMSR less than 0.08 (Hair, Anderson, Tatham, & Black, 1998; et al., 1998; Joreskog & Sorbom, 1993). Figure 2 shows the structural
Joreskog & Sorbom, 1993). An assessment of the measurement model with the coefficients for each path (hypothesized relation-
model suggested an acceptable model fit (GFI = 0.954; AGFI = 0.912; ship), and with solid and dashed lines indicating a supported
CFI = 0.956; NFI = 0.939; RMSEA = 0.042). and unsupported relationship respectively. With the exception
To assess the reliability of the constructs, composite reliability of H4 ( = 0.139, t = 0.898, p > 0.05) and H7 ( = 0.239, t = 2.751,
(CR) was used. All of the composite reliability values, ranging from a p < 0.01) all other hypothesized relationships are supported. In
low of 0.910 to a high of 0.932, exceeded the recommended cut-off particular, dysfunctional conflict is positively associated with infor-
value of 0.7. A variable’s squared multiple correlation (SMC) is the mation sharing, rather than negatively related as hypothesized
proportion of its variance that is accounted for by its predictors. The in H7. Relational benefits (H1: = 0.281, t = 7.142, p < 0.001; H2:
average variance extracted (AVE) was greater than 0.5 in all cases, = −0.912, t = −3.836, p < 0.001) are significantly associated with
meaning that the variance accounted for by each of the constructs relational proclivity and power symmetry. Relational proclivity
was greater than the variance accounted for by the measurement (H3: = 0.682, t = 4.817, p < 0.001) is significantly associated with
error (Fornell & Larcker, 1981; Hair et al., 1998; Joreskog & Sorbom, connectedness. Connectedness (H5: = 0.492, t = 3.869, p < 0.001)
1993). In addition, an assessment of discriminant validity between is significantly associated with information sharing. Power symme-
the constructs supported the model fit. Table 4 summarizes the try (H6: = −0.701, t = −6.892, p < 0.001) is significantly associated
assessment results of the measurement model. with dysfunctional conflict. Overall, the model explains 16.6% of
the variance in relational proclivity, 11.7% in power symmetry,
49.3% in connectedness, 9.6% in dysfunctional conflict, and 53.5%
5.2. Assessment of the structural model in information sharing.

Table 5 shows the inter-correlations between the six con- 5.5. Test of mediating effects
structs of the structural model. The overall fit of the structural
model is acceptable, since all measures of fit reach an accept- This paper followed the procedure suggested by Baron and
able level ( 2 = 120.13, df = 432, ˛ = 0.01; GFI = 0.911; AGFI = 0.872; Kenny (1986), Gelfand, Mensinger, and Tenhave (2009) and Ke,
CFI = 0.933; NFI = 0.917; RMSEA = 0.071). Liu, Wei, Gu, and Chen (2009) and tested the mediating effects
of the model, as shown in Table 6. The direct links between rela-
tional benefits and both connectedness and dysfunctional conflict,
5.3. Common method bias between relational proclivity and information sharing, between
power symmetry and information sharing, and between connect-
Following the suggestion of (Podsakoff & Organ, 1986), Har- edness and information sharing were significant and thus satisfied
mon’s one-factor test was run to ensure that common method the first condition for mediating effect. The link between connect-
variance did not account for our findings. Unrotated principal com- edness and information sharing was not significant. The second
ponents analysis revealed six factors with eigenvalues greater than condition for mediating effect was thus not satisfied; therefore,
1, which accounted for 73.7% of the total variance. The first factor dysfunctional conflict did not mediate the relationship between
did not account for the majority of the variance (23.2%). As no single connectedness and information sharing. In contrast, the links
factor emerged that accounted for most of the variance, common between relational benefits and both relational proclivity and
method bias does not appear to be a problem in the study. power symmetry, between relational proclivity and connectedness,


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Table 5
Correlation matrix of constructs.

(A) (B) (C) (D) (E) (F)

(A) Relational benefit (RB) 1.000
(B) Power symmetry (PS) −0.251*** 1.000
(C) Relational proclivity (RP) 0.649*** −0.088 1.000
(D) Connectedness (CO) 0.144 −0.059 0.427*** 1.000
(E) Dysfunctional conflict (DC) 0.069 −0.342*** 0.049 0.136 1.000
(F) Information sharing (IS) 0.173 −0.123 0.431*** 0.685*** 0.293*** 1.000
***
Significance at ˛ = 0.001.

Table 6
Results of mediating effect tests.

Coefficient in regressions

IV M DV IV → DV IV → M IV + M → DV Mediating

IV → DV M → DV

RB RP CO 0.244*** 0.281*** 0.052 0.682*** Full
PS DC 0.744*** −0.912*** 0.104 −0.701*** Full
RP CO IS 0.512*** 0.682*** 0.147 0.502*** Full
PS DC IS −0.280*** −0.701*** −0.112 0.239** Full
CO DC IS 0.535*** 0.139 0.502*** 0.239** Not

Note 1:
**
***
Note 2: IV, independent variable; M, mediator; DV, dependent variable. Step 1: IV → DV is significant. Step 2: IV → M is significant. Step 3: IV + M → DV. (a) If M is significant
and IV is not significant, then M has full mediating effects. (b) If both M and IV are significant, then M has partial mediating effects.

and between power symmetry and dysfunctional conflict were all indicates that organizations tend to collaborate together if they per-
significant. As such, they satisfied the second condition for the ceive cooperation with each other will bring benefits and reinforce
existence of mediating effects. Furthermore, the direct relation- information sharing. As suggested by previous studies (Johnson &
ships relational benefits and both connectedness and dysfunctional Sohi, 2001; Larson, 1992), when there is stronger relational pro-
conflict, between relational proclivity and information sharing, clivity within organizations, the relationship between partners will
and between power symmetry and information sharing became be more intimate, and the degree of connectedness will also be
insignificant when we added the link between relational bene- elevated. The performance of relational benefits and power sym-
fits and both relational proclivity and power symmetry, between metry among organizations was quite negative, but significant –
relational proclivity and connectedness, between power symmetry a result also in accordance with the findings of previous studies
and dysfunctional conflict, between connectedness and dysfunc- (Morgan & Hunt, 1994). In line with Lin and Germain (1998), greater
tional conflict, between power symmetry and information sharing, power symmetry and dysfunctional conflict among organizations
and between connectedness and information sharing, respectively, will cause a negative but significant effect. When the power is
while the latter links were significant. Therefore, the results show asymmetric, the weaker party will propose some actions regarding
that relational proclivity fully mediated the relationship between dysfunctional conflict to adjust the imbalanced situation. Morgan
relational benefits and connectedness. Power symmetry fully medi- and Hunt (1994) also declare that an imbalance in power causes
ated the relationship between relational benefits and dysfunctional dysfunctional conflict.
conflict. Connectedness fully mediated the relationship between If parties of an inter-organizational relationship, such as man-
relational proclivity and information sharing. Also, the relation- ufacturers and subcontractors, can maintain power symmetry in
ship between power symmetry and information sharing was fully the cooperation relationship, there will be no negative action
mediated by dysfunctional conflict. caused by power asymmetry. Even though these negative actions
will not provoke any negative result to the collaboration, power
6. Discussion asymmetry is the fatal factor that causes the termination of
relationships. Therefore, for successful partner-type relationships
Conforming to the hypothesis, relational benefits have the partners should design and plan collaboration agreements metic-
strongest positive influence on relational proclivity. This result is ulously, and strive for power symmetry in order to avoid creating
consistent with Gwinner et al. (1998) and Wulf et al. (2001). This unnecessary problems. Connectedness was insignificant but pos-

Relational Proclivity Connectedness

0.682***
0.281*** 0.502***

Relational Benefit Information
0.139 Sharing

0.239**
-0.912***
Power Symmetry Dysfunctional Conflict
-0.701***

Fig. 2. The structural model. **Significance at ˛ = 0.01; ***Significance at ˛ = 0.001.


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itively associated with dysfunctional conflict. This suggests that conflict not only are consistent with prior studies, but also
dysfunctional conflict between organizations in information shar- examine how information sharing is significantly affected by
ing might be unavoidable despite strong connectedness. inter-organizational relational benefits through other mediating
Information sharing behavior is positively associated with dys- variables such as relational proclivity, and connectedness, power
functional conflict. This finding of the model is noteworthy. The symmetry, and dysfunctional conflict. Specifically, the results indi-
positive influence of dysfunctional conflict on information sharing cate that relational benefits affect inter-organizational information
is a new finding. One possible reason is that the relational bene- sharing through its positive influence on relational proclivity and
fits of the parties involved are so great that dysfunctional conflict connectedness. In contrast, the effects of relational benefits on
among them is tolerated and conceived of as acceptable for achiev- inter-organizational information sharing are mediated by its nega-
ing better information sharing. A firm should carefully go through tive influence on power symmetry. Enhanced by relational benefits,
the process of estimating its partners. For example, one party from which is related to relational resources, the development of con-
the cooperation relationship could be the net-gainer at any one nectedness will surely have some positive effects on subsequent
time. Therefore, there would be no cut-and-run because the party information sharing and negative effects on dysfunctional conflicts
perceives that only through continuity of collaboration can gains between the firms, because some positive discussions and con-
be achieved in the future (Dodgson, 1993). structive ideas and opinions would be expressed freely between
As for disagreements, they can take place in any relationship them. The important managerial implication is that a good practice
because they are inevitable. If both parties perceived disagreements in enhancing information sharing in supply chains is to develop a
as a means to bring out problems instead of arousing disputes, positive and strong connectedness (i.e. opportunities to interact,
this would be a positive element in the relationship (Morgan & assistance for each other, and channels for communication).
Hunt, 1994). According to Wilson (1995), a structural bond would The vast majority of the literature reviewed in studying informa-
make it hard for collaborated members to terminate the relation- tion sharing in supply chains has taken analytical and/or simulation
ship because non-retrievable investments costs, adaptations, and approaches (Huang et al., 2003). Rather than focusing on these fac-
shared valuable information would have already reached a cer- tors that directly affect the behaviors of information sharing, this
tain level. Therefore, it would be hard for collaborated members to empirical research reveals how information sharing is significantly
withdraw from the relationship even though severe disagreements affected by inter-organizational relational benefits through other
might occur at times. mediating variables. The advantage of the empirical approach in
According to the returned questionnaires of this study, the main this paper is that it can account for the impacts of the real-world
subjects that manufacturers and subcontractors collaborate on are environment, rather than one that takes analytical and/or simula-
technology transfer, development of new technology and prod- tion approaches, and gain a more complete understanding of the
ucts. These constituted 46.97% of the collaborated items, showing cause-and-effect relationships of organizational behaviors within
that almost half of the collaborated items are R&D. Work regard- the supply chain systems. Existing empirical research on this issue
ing R&D requires a huge amount of human resources, machines, has focused on the antecedents to information sharing, as shown in
time and a handsome sum of money to produce greater profits and Table 1, thus forgoing the opportunity to have an in-depth under-
positive cooperation. Even though there are severe disagreements standing of the influencing processes of these factors. Therefore,
between firms, it is possible for them to tolerate dysfunctional the current study enriches the literature on the implications that
conflict because connectedness, namely, the cost that has been the interrelationship between relational benefits and dysfunctional
invested in the relationship, is formed. conflict has for effective information sharing in supply chain man-
Environmental pressures and organizational culture may be agement.
another possible reason for the positive relationship between This study contributes to supply chains research by integrating
dysfunctional conflict and information sharing. According to the the perspective of relational view (such as RBV, political economy
institutional theory, institutional pressures can be exerted on the perspective and relational risk) in the study of the relational gov-
firm by the institutional environments formally through rules or ernance in supply chains. This paper extends current research by
laws, or informally through certain cultural expectations (Amis, highlighting the role of value-based relationships from the rela-
Slack, & Hinings, 2002; DiMaggio & Powell, 1983; Ke et al., 2009; Liu, tional view of partners. To enhance the relational value of relational
Ke, Wei, Gu, & Chen, 2010; Teo, Wei, & Benbasat, 2003). Violating governance and to diminish the relational risk of relational gov-
these rules may bring a firm’s legitimacy into question and jeopar- ernance when information sharing is involved, relevant parties
dize its access to scarce resources and social support (DiMaggio & should develop value-based relationships by focusing on activi-
Powell, 1983; Liang, Saraf, Hu, & Xue, 2007; Tolbert, 1985). Thus, ties that would enhance mutual benefit and interdependence (such
the firm will choose to conform to institutional pressures to avoid as relational benefits and connectedness) and avoid activities that
being locked out of cooperative relationships and to ensure access would reinforce the probability of relational risk behaviors (such
to relational resources such as relational benefits. The concept of as power symmetry and dysfunctional conflict). The findings of
organizational culture refers to a collection of shared assumptions, the study provide practical insights in understanding how supply
values, and beliefs that is reflected in organizational practices and chain members should reinforce their collaborative behaviors and
goals and that helps its members understand organizational func- activities that would improve their relational benefits and connect-
tioning (Deshpandé, Farley, & Webster, 1993; Khazanchi, Lewis, edness and in turn enhance information sharing for achieving the
& Boyer, 2007; Lewis & Boyer, 2002; Liu et al., 2010; White, competitive advantage of supply chains as a whole.
Varadarajan, & Dacin, 2003). In line with organizational behavior
literature, organizational culture can impact managers’ ability to
process information, rationalize, and exercise discretion in their 7. Conclusions and future research
decision-making processes (Berthon, Pitt, & Ewing, 2001; Liu et al.,
2010; Oliver, 1991). As such, institutional pressures could signifi- It is of strategic importance for an organization to understand
cantly impact a firm’s decision even though severe disagreements the factors influencing the development and implementation of
might occur at times, and the firm’s organizational culture may information sharing with its partners in an inter-organizational
moderate such impacts. relationship such as supply chains. In this paper, we developed a
Our findings on the effects of relational benefits, relational research model to examine the role played by inter-organizational
proclivity, connectedness, power symmetry and dysfunctional relational benefits, relational proclivity, connectedness, power


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Carnegie Mellon University.
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