Ck

YA

a

AA

KSKCE

1

dTkctts2

laaaacanflt

0d

Journal of Operations Management 29 (2011) 128–142

Contents lists available at ScienceDirect

Journal of Operations Management

journa l homepage: www.e lsev ier .com/ locate / jom

o-opetition, distributor’s entrepreneurial orientation and manufacturer’snowledge acquisition: Evidence from China

uan Li, Yi Liu ∗, Heng Liuntai College of Economic & Management, Shanghai Jiaotong University; School of Management, Xi’an Jiaotong University, Xi’an, 710049, Shaanxi, PR China

r t i c l e i n f o

rticle history:vailable online 23 July 2010

eywords:upply chain knowledge managementnowledge acquisitiono-opetition relations

a b s t r a c t

By viewing cooperation and different types of conflicts as “co-opetition” factors in a manufacturer–distributor supply chain, this paper provides a conceptual model for examining the effects of cooper-ation and conflicts on a manufacturer’s knowledge acquisition process and for exploring the moderatingeffects of a distributor’s entrepreneurial orientation on the relationships between co-opetition factorsand the manufacturer’s knowledge acquisition. This conceptual model is tested with 225 dyad samplesfrom manufacturer–distributor supply chains in China. The results show that cooperation and the type

ntrepreneurial orientationof conflict have both individual and interactive effects on the manufacturer’s knowledge acquisition,thus highlighting the importance of the co-opetition perspective on supply chain knowledge manage-ment. More importantly, the results show that the entrepreneurial orientation of a distributor positivelymoderates the relationships between co-opetition factors and a manufacturer’s knowledge acquisition,implying that strengthening the distributor’s entrepreneurial orientation can improve the efficiency ofco-opetition and thereby affect the knowledge acquisition of the manufacturer, and highlighting theimportance of blended analysis across the domains of supply chain management and entrepreneurship.

. Introduction

Knowledge has become recognized as a key issue thatefines competitive advantage (Nonaka et al., 1996; Grant, 1996).herefore, firms have increasingly paid attention to enhancingnowledge acquisition by improving the efficiency of supply chainooperation (Skinner et al., 1992; Burkink, 2002). One approacho advancing knowledge acquisition, from organizational learningheory, focuses on the properties of dyadic relationships betweenocial organizations, such as cooperation and conflict (Song et al.,005; McEvily et al., 2003).

Previous literature relating to this approach has often high-ighted the impact of either cooperation or conflict on knowledgecquisition (Muthusamy and White, 2005; Paulraj et al., 2008; Lylesnd Salk, 1996; Yin and Bao, 2006). Researchers from the cooper-tion perspective have tended to focus on knowledge acquisitionssociated with a higher level of integration of physical and humanapital resources across the supply chain (Argyle, 1991; Paulraj et

l., 2008). Scholars from the conflict management perspective haveoted that conflict includes both constructive and destructive con-ict. Constructive conflict is defined as an evaluative appraisal ofhe results of recent efforts to manage disagreements (Rawwas et

∗ Corresponding author. Tel.: +86 29 8266 5029; fax: +86 29 8266 8382.E-mail address: liuyi@mail.xjtu.edu.cn (Y. Liu).

272-6963/$ – see front matter © 2010 Elsevier B.V. All rights reserved.oi:10.1016/j.jom.2010.07.006

© 2010 Elsevier B.V. All rights reserved.

al., 1997; Anderson and Narus, 1990; Song et al., 2006; Tjosvoldand Su, 2007; Eckert and Rinehart, 2005). Destructive conflict isviewed as the result of the influence of strong forces that push theparties toward increasingly hostile behavior (Thomas, 1976). Thesetwo kinds of conflict either contribute to or impede knowledgeacquisition (Rawwas et al., 1997; Song et al., 2006).

New advances in this domain indicate that the properties ofa supply chain partnership can be best described as co-opetition(Bengtsson and Kock, 2000; Kotzab and Teller, 2003; Luo, 2007),defined as cooperation and competition simultaneously function-ing between increasingly interdependent parties (Brandenburgerand Nalebuff, 1996; Lado et al., 1997), and the balance betweencooperation and competition can evolve into an important rela-tional capability (Gnyawali et al., 2006). Therefore, the two differentfacets of the co-opetition relationship (cooperation and conflict)might have individual as well as interactive impacts on theinter-organizational knowledge acquisition process. However, theinteraction between cooperative behavior and conflictive behaviorthat affects a manufacturer’s knowledge acquisition has receivedlittle attention in prior literature.

More importantly, there has been increasing interest in the

intersection between supply chain management and entrepreneur-ship (Arend and Wisner, 2005; Giunipero et al., 2005). The approachthat focuses on the properties of dyadic relationships in supplychain management can be extended by also exploring the effectsof entrepreneurship in this supply chain (Walter et al., 2006).

ns Ma

Inictprttfwtitdpibae

mfl(ttsacuEdokmiketmte

rscHtttmt

tapaeeidfwtia

Y. Li et al. / Journal of Operatio

n particular, since the entrepreneurial orientation (EO) of part-ers impacts the potential benefits from the co-opetition relations,

t should interact with the co-opetitive behavior of the firms tohange the efficiency of their knowledge acquisition. In fact, dis-ributors with a high level of EO are usually more innovative androactive in product market domains and prefer to take moreisks in a co-opetitive relationship with a manufacturer in ordero improve their competitive advantage, and this preference inurn changes the potential benefits that manufacturers can realizerom the supply chain co-opetition (Zahra et al., 1999). Co-opetitingith such a distributor can probably offer the manufacturer a bet-

er chance to access wider areas of market information. Therefore,t is possible that the partner’s EO not only impacts the poten-ial benefits from the co-opetition relations (Mione, 2009) but alsoetermines the efficiency of the recipient’s knowledge acquisitionrocess in response to different co-opetition relations. Thus, it is

mportant to study how a partner’s EO moderates the relationshipetween co-opetition relations and a manufacturer’s knowledgecquisition. Unfortunately, existing literature provides little knowl-dge about this important issue.

To address these gaps, this study operationalizes a conceptualodel which links cooperation, constructive vs. destructive con-

ict, distributor’s EO and manufacturer’s knowledge acquisitionMKA) holistically to provide the following contributions. From aheoretical viewpoint, drawing upon the co-opetition perspective,his study argues that the properties of a supply chain partner-hip can be described as co-opetition, and the cooperation behaviornd two types of conflict behaviors (constructive and destructiveonflict) may have individual and interactive effects on the man-facturer’s knowledge acquisition. Furthermore, by leveraging theO lens into the operations management study, we explain how aistributor partner’s EO provides an exogenous moderating effectn the relationship between co-opetition and the manufacturer’snowledge acquisition, thereby showing that, by leveraging theoderating effect of the distributor’s EO, the manufacturer can

mprove the efficiency of the co-opetition which in turn affectsnowledge acquisition. Therefore, we incorporate the distributor’sntrepreneurship as an external resource to create complemen-ary assets with internal co-opetition capability to improve the

anufacturing firm’s knowledge acquisition, thereby extendinghe supply chain co-opetition perspective by incorporating thentrepreneurship lens.

Meanwhile, some recent strategic supply chain managementesearch has emphasized the importance of simultaneously con-idering strategic and operational issues when coping with supplyhain issues (Hult et al., 2004; Upson et al., 2007; Li et al., 2008a,b).owever, few empirical studies of this subject have been under-

aken. By jointly considering the operational issues (maintaininghe co-opetition balance) and the strategic issues (finding a dis-ributor partner with high entrepreneurial orientation) in the

anufacturer–distributor supply chain, this study has the potentialo enrich the literature in this stream.

Moreover, in contrast with previous entrepreneurship litera-ure which has mainly paid attention to the impact of a firm’s EOnd the ways in which the supply chain can be leveraged to sup-ort the requirements of EO (e.g., Handfield et al., 2009; Walter etl., 2006), this study analyzes how the firm’s partner’s EO influ-nces the efficiency of co-opetitive relations. This emphasis thusxtends research in entrepreneurship from intra-organization tonter-organization analysis. We especially argue that the EO of aistributor partner can differently moderate the effects of a manu-

acturer’s co-opetitive behaviors on its knowledge acquisition, ande examine the potential fit between co-opetitive strategies and

he partner’s characteristics (EO) in the inter-organizational learn-ng process. Furthermore, viewing a partner’s strategic orientations an important external resource, we argue that the distributor’s

nagement 29 (2011) 128–142 129

EO and the co-opetition of the manufacturer can exploit com-plementary assets to improve the knowledge acquisition process.By combining the EO perspective, the co-opetition perspectiveand the complementary asset perspective (Teece, 1986; Song etal., 2005), this study explains important complementary relation-ships between the distributor’s EO as an external resource andthe manufacturer’s co-opetition as an internal behavior, an expla-nation which extends the complementary asset perspective intothe inter-organizational cooperation analysis such as supply chaincooperation.

From an empirical viewpoint, we investigate the above ques-tions in the context of a Chinese manufacturer–distributor supplychain. China is the largest emerging economy and the world’s man-ufacturing center for consumer products (Jiang et al., 2007; Liu etal., 2009; Zhao et al., 2007; Flynn et al., 2007), and the great com-petitive pressures and escalating customer expectations in Chinaare forcing manufacturers to rely heavily on distributors’ knowl-edge in order to develop attractive products and take advantageof market opportunities (Ambler et al., 1999; Zhao et al., 2008;Boyer and Lewis, 2002; Xu et al., 2006). Thus, the question of howto enhance the manufacturer’s market responsiveness has becomean important issue in China (Langerak, 2001; Zhu and Sarkis, 2004;Ianchovichina and Martin, 2004). Meanwhile, consistent with theco-opetition perspective, the cultural tradition of ‘yin-yang philos-ophy’ (Strutton and Pelton, 1997; Chen, 2002) may have additionalimplications for current Western operations management theory toapply in this new setting. The Chinese ‘middle ground’ philosophy,with its emphasis on balance and the integration of opposites, offerspromise for enriching conventional Western conceptions of supplychain relationship management (Chen, 2008). At the same time theChinese are known for their entrepreneurial skills (Hofestede andBond, 1988; Chen, 2008), and entrepreneurs by nature tend to useappropriate co-opetitive relationships to find new ways of doingbusiness. Our empirical findings, based on 225 dyadic Chinese firmsamples, provide support for our conceptual model.

2. Theoretical background and conceptual model

2.1. Co-opetition perspective in supply chain knowledgemanagement

Research on knowledge management, both within and amongfirms, has been widely diverse, but the theoretical explanations canbe generally organized according to the properties of the threecontexts within which knowledge management occurs: proper-ties of units (e.g., an individual, or an organization), propertiesof knowledge, and properties of the relationships between units(Argote et al., 2003). Compared to research on how properties offirms and properties of knowledge affect acquisition outcomes,research on how properties of relationships between organizationsaffect learning and knowledge management outcomes is a newerapproach (Argote et al., 2003). The positive aspects of relationalproperties, such as strength of connection, trust, and cooperation,as well as the negative aspects such as conflict and opportunism,and their effects on the outcomes of knowledge acquisition ininter-organizational relations have been analyzed extensively inthe literature on knowledge management, strategic managementand operations management (e.g., Muthusamy and White, 2005;Paulraj et al., 2008; Lyles and Salk, 1996; Yin and Bao, 2006; Songet al., 2006).

The co-opetition perspective, which emphasizes that coopera-tion and competition function simultaneously (Brandenburger andNalebuff, 1996; Lado et al., 1997), is the most recent advance insupply chain knowledge management. Strategic interdependencebetween manufacturers and distributors contains both cooperating

1 ns Ma

afaqtgaCafit(uiiTflaa

vdaflsabacadc(

mcSamcecdeacoadlsa

fisFcetwotr2ow

30 Y. Li et al. / Journal of Operatio

nd bargaining elements (Young and Wilkinson, 1997). Manu-acturers and their distributor partners cooperate in order tochieve common and compatible goals such as reliable productuality, timely delivery and attractive price, while at the sameime they conflict with each other with respect to incompatibleoals such as favorable payment terms and advantageous financialrrangements (Rawwas et al., 1997; Young and Wilkinson, 1997).ooperation means the joint operation or action, or assistancend teamwork, and the cooperating elements that can provide arm with opportunities to learn from its partners and gain accesso complementary resources beyond the firm’s own boundariesPowell, 1987; Flynn et al., 2010). Meanwhile, conflict refers to sit-ations described by an expressed struggle between two or more

nterdependent parties with apparently incompatible goals, lim-ted resources, and a perception of interference (Thomas, 1992).he parties in a cooperative arrangement may also encounter con-icts arising from different motivations, inconsistent goals or anbsence of mechanisms mitigating possible opportunism (Webbnd Hogan, 2002; Khanna et al., 1998).

By examining only cooperation and ignoring conflict, or viceersa, existing research explains only part of the overall picture ofyadic relations, while the new co-opetition perspective takes intoccount the simultaneous occurrence of both cooperation and con-ict (e.g., Bengtsson and Kock, 2000; Eriksson, 2008). In fact, unlessupply chain members refuse to cooperate at all, conflict is unavoid-ble. Cooperation usually indicates that cooperating actions occuretween two originally separate entities, and effective knowledgecquisition and performance advancing requires firms in supplyhain to unify cooperation from external participants (Vickery etl., 2003). However, since they are independent entities, cognitiveifferences always exist in their goals, interests and resource allo-ation, and these differences or contradictions may cause conflictEliashberg and Michie, 1984).

Existing literature on supply chain management suggests thatanagerial goals should be to minimize conflict and maximize

ooperation (e.g., Mallen, 1963; Skinner et al., 1992; Reve andtern, 1979; Stern and Reve, 1980). However, since cooperationnd conflict mutually co-exist, we argue that the proper way toanage a co-opetition relationship is not to completely minimize

onflict but to manage constructive and destructive conflict differ-ntly. In fact, in view of the different features of the two kinds ofonflict, constructive conflict and destructive conflict should haveifferent effects on aspects of firm performance such as knowl-dge acquisition. Further, because cooperation and conflict exist insupply chain simultaneously, we argue that the interactions of

ooperation and two types of conflict have an important impactn a manufacturer’s knowledge acquisition. In other words, man-ging supply chain relations both to focus on cooperation and toeal with constructive conflict can be a relational capability which

eads to highly efficient knowledge acquisition from partners inupply chains and therefore can be a source of firm’s competitivedvantage.

Meanwhile, in an inter-organizational cooperation process,rms with strong EO place more emphasis on knowledge acqui-ition from partners through co-opetition activities (Hardy, 2009).irst, such firms emphasize learning from partners so that theyan obtain advanced knowledge from novel innovation (Yli-Renkot al., 2001). During this learning process, these firms prefer toake proactive actions in both the cooperation and the competitionith their partners (Mione, 2009) so that they can grasp market

pportunities early. Second, these firms often emphasize acquisi-

ion of external knowledge and therefore might experience risksesulting from conflicts in cooperation with partners (Hitt et al.,001). In such a case, the firms focus more on use of the benefitsf co-opetition in knowledge acquisition (Luo, 2005). Therefore,e argue that firms with strong EO should strengthen their co-

nagement 29 (2011) 128–142

opetition behavior for the purpose of acquiring knowledge fromtheir partners.

Moreover, the yin-yang philosophy, deeply rooted in East Asianculture, aligns with the spirit of co-opetition relations (Strutton andPelton, 1997; Luo, 2005). Cooperation represents yang factors, andconflict represents yin factors. Unlike polar-oriented thinking, theyin-yang philosophy is based upon the simultaneous considerationof both sides of one thing and their possible mutual conversionsand synergies (Strutton and Pelton, 1997; Wong and Tam, 2000),and is therefore consistent with the co-opetition perspective (Chen,2008). Thus, in the Chinese context, manufacturers who followa yin-yang philosophy concerning supply chain relational man-agement simultaneously deal with both the cooperation and theconflict issues, so that they can more efficiently obtain importantknowledge from distributor partners.

2.2. The moderating role of the distributor’s EO

Researchers are beginning to recognize that the relationshipbetween properties of dyadic relationships and outcomes may becontingent on some contextual factors (Argote et al., 2003; Burtonet al., 2002). For example, Das (2003) demonstrates that the fitbetween characteristics of a problem and the problem-solvingapproaches predicts performance. Sorenson (2003) suggests thatthe fit between market turbulence and firm design predicts thefirm’s probability of survival. Similarly, in accord with increasinginterest in the interface between supply chain management andentrepreneurship, we suggest that the analysis of a dyadic rela-tionship can be extended by exploring the effect of EO in thisrelationship.

Entrepreneurial orientation (EO) describes a firm’s tendencyto pursue new entry opportunities and to focus on gaining com-petitive advantage principally through risk-taking, innovative andproactive behavior (Miller, 1983; Lumpkin and Dess, 1996; Dess etal., 2005; Li et al., 2008a,b). Scholars who treat EO as a key firm char-acteristic have found that businesses with high EO perform better(e.g., Wiklund, 1999; Zahra and Covin, 1995). The application ofentrepreneurial concepts as a lens to study supply chain manage-ment is in a nascent stage, yet some recent studies lend credibilityto this theoretical advance. For example, Handfield et al. (2009)provide a basis for the contention that entrepreneurial behavioris an important attribute for firms to adopt in building a supplychain team. Walter et al. (2006) argue that since pursuing EO is aresource-consuming process, a firm’s supply chain capability maymoderate the relationship between the firm’s EO and performance.An interesting but rarely mentioned issue is the role of the distrib-utor partner’s EO in this dyadic relation. By analyzing the impactof a partner’s EO, this paper extends the focus from firm-level EOto supply chain-level EO and examines the potential fit betweenco-opetitive strategies and the partners’ EO in the learning processof a supply chain.

Meanwhile, finding a distributor partner with a particularstrategic orientation is an important strategic issue to considerwhen managing supply chains in the current global economic cli-mate. Depending on its strategic orientation, a distributor maynot only differently influence behavior in co-opetition interac-tions between members but also differently affect the contentand quality of the knowledge it can possibly transfer (De Clerqand Rangarajan, 2008). Therefore, by jointly considering the directimpacts of co-opetition behavior and the moderating effects of thedistributor’s EO on this co-opetition behavior, this study can give

a more thorough explanation about how a manufacturer can learnvaluable knowledge from a distributor partner.

Moreover, the complementary asset perspective suggests thatwhen different resources in a firm exploit complementary rela-tions, they can produce synergy to improve firm performance

Y. Li et al. / Journal of Operations Management 29 (2011) 128–142 131

ceptu

(dciceta

pt2eofairmactk

Ftkp

3

3

lrIgfimstdnibtac

Fig. 1. Con

Teece, 1986; Song et al., 2005). Such synergy reduces the resourceeficiency and generates new applications from those resourceombinations (Song et al., 2005). Extending this viewpoint fromntra-organization to inter-organization, we argue that firms canombine their internal capabilities (co-opetition capability) withxternal resources (distributor’s EO) and thereby can influencehe efficiency of internal capabilities to formulate complementaryssets and thus improve their knowledge acquisition.

Furthermore, a distributor with high EO might have a higherroclivity for choosing a co-opetitive interaction with a manufac-urer as a way to pursue new market opportunities (De Clercq et al.,010). By responding to various co-opetitive relationships differ-ntly, distributors with different levels of EO have different impactsn the applicability of the manufacturer’s co-opetitive strategiesor acquiring market knowledge. In this way, the distributor’s EOs an external resource can not only change the content and qual-ty of knowledge, but can also change the efficiency of co-opetitionelations. Thus, we argue that the distributor’s EO as an importantoderator can strengthen the relationship between co-opetition

nd the manufacturer’s knowledge acquisition, thus explaining theomplementary effect between the co-opetition of the manufac-urer and the distributor’s EO in improving the manufacturer’snowledge acquisition.

From the above discussion, we provide a conceptual model inig. 1 to explain the relationships among cooperation, construc-ive and destructive conflict, distributor’s EO, and manufacturer’snowledge acquisition in a Chinese manufacturer–distributor sup-ly chain.

. Hypothesis development

.1. Cooperation and the manufacturer’s knowledge acquisition

Cooperation is an important issue in an inter-organizationalearning process and a key characteristic of the properties of dyadicelations (e.g., Muthusamy and White, 2005; Paulraj et al., 2008).n such a context, manufacturers and distributors become strate-ic partners, share risks and benefits, exchange operating andnancial information, are jointly involved in continuous improve-ent and new product development programs, and make their

uccess interdependent (Albino et al., 2007). As we can see fromhis illustration, the connotation of cooperation involves manyifferent issues in the collaborative behavior of supply chain part-ers (Evangelista and Hau, 2009), such as joint problem solving,

nformation exchange, benefit sharing, and cross-boundary teamuilding. Different from this broad conception, however, in this par-icular study cooperation means the integration of a manufacturer’snd a distributor’s physical and human capital as well as the relatedoordination activities for the purpose of pursuing common or com-

al model.

patible goals (Argyle, 1991; Seuring and Muller, 2008), similar tothe notion of supply chain integration (Zhao et al., 2008; Vickeryet al., 2003; Droge et al., 2000). The essence of this cooperativebehavior is the recognition that members from each supply chainpartner perform tasks collaboratively (Evangelista and Hau, 2009).We expect that a positive relationship exists between cooperationand a manufacturer’s knowledge acquisition for two reasons.

First, high level cooperation facilitates communication oppor-tunities between a manufacturer and a distributor partner. Forinstance, Herrgard (2000) points out that face-to-face interactionamong employees from different organizations is often considereda prerequisite for the diffusion of tacit knowledge. Through face-to-face interaction, partners communicate with each other usinglanguages they both are familiar with, in order to solve problemscollaboratively (Herrgard, 2000). Also, Solingen et al. (2000) notethat by working as cross-border teams, supply chain members havea better chance to observe and reflect on the practices of the otherfirms. Thus, cooperation facilitates both verbal as well as non-verbalcommunication through which the firms can share both tacit andexplicit knowledge.

Second, cooperation enhancement also reveals voluntarybehavior for solving a partner’s problems, behavior which mayin turn lead to reciprocal behavior such as information-sharing.Today’s behavior in support of the other firm’s requirements mightlead to tomorrow’s reciprocity (e.g., Das and Teng, 2002). Specif-ically, under Chinese reciprocal business norms, if a distributorperceives that a manufacturer’s cooperative behavior in prior trans-actions has been supportive (such as providing equipment andemployees in times of need), the distributor may then contributemore to the exchange of information in return. Meanwhile, thecooperative behavior may also improve the personal attachment(the guanxi in Chinese) between channel members (Zhao et al.,2007; Leung et al., 2005; Tjosvold and Su, 2007), which may con-tribute to the high level of inter-firm knowledge transfers andimprove the knowledge acquisition. Therefore, we suggest:

Hypothesis 1. Cooperation between a manufacturer and a dis-tributor is positively related to the manufacturer’s knowledgeacquisition.

3.2. Conflict and manufacturer’s knowledge acquisition

Conflict between a manufacturer and a distributor, indicative ofdisagreement concerning goals and/or operational or managerialexpectations, is another key feature that characterizes dyadic rela-

tions, and is believed to affect knowledge acquisition as well, butin different ways (e.g., Lyles and Salk, 1996; Yin and Bao, 2006).In a manufacturer–distributor supply chain characterized by highconstructive conflict, manufacturers and distributors often havedifferent opinions about how a task is done and how to find a

1 ns Ma

csiwatcst

trbSalptTatiotpcwaktt

Haa

adctdicclv

kfwatlawttdiTaomt

32 Y. Li et al. / Journal of Operatio

ompatible solution. This type of conflict is also treated as discus-ion, bargaining, debate, or a win–win approach toward conflict,n which the participants discuss together to ensure that the best

ay to perform the current task is agreed upon (e.g., Rawwas etl., 1997; Song et al., 2006; Tjosvold and Su, 2007). We use theerm ‘constructive’ to refer to a conflict which has more gains thanosts—one that draws people together, strengthens their relation-hip (by redefining it in a more appropriate or useful way) and leadso a positive change in all the firms involved.

We expect that a positive relationship exists between construc-ive conflict and a manufacturer’s knowledge acquisition for twoeasons. First, constructive conflict can promote creative solutionsy providing varieties of thinking directions (Hoffman et al., 1962;ong et al., 2006). Although there exist divergent perspectivesbout how to best solve channel problems, the manufacturer caneverage the constructive conflict by joining in the open discussionrocess to promote fresh thinking and to find transcendent solu-ions to complex problems (Tjosvold et al., 2001; Leung et al., 2002;josvold and Su, 2007). Mahoney (1993) also indicates that intensend enthusiastic discussions can lead employees in cross-bordereams to go beyond current ways of screening problems by engag-ng in a conversation across paradigms and disciplines. Second,rganizations can more deeply understand their partner’s atti-ude, competence and sincerity through this constructive conflictrocess. For example, Tjosvold et al. (2003) argue that discussingonflict issues openly and constructively not only helps peopleork effectively, but also leads them to better evaluate each other’s

bilities and attitudes. In such cases, each party in the cooperationnows more about the profiles of both the cooperative situation andhe partner, thereby helping to facilitate knowledge acquisition byhe manufacturer. Thus, we suggest:

ypothesis 2a. Constructive conflict between a manufacturer anddistributor is positively related to the manufacturer’s knowledgecquisition.

In contrast, in manufacturer–distributor supply chains char-cterized by high destructive conflict, both manufacturers andistributors feel dislike and suspicion about each other as theonsequence of unhealthy behavior that has occurred duringhe conflict process. This type of conflict is also treated asomination, control, or a win-lose approach toward conflict,

n which each conflict participant tries to ensure that its ownlaims succeed. Destructive conflict often has largely negativeonsequences—pushing people apart, destroying relationships, andeading to negative consequences including an escalation of fear,iolence and distrust.

Such destructive conflict can decrease the manufacturer’snowledge acquisition for two reasons. First, destructive conflict isound to be related to the deterioration of the parties’ satisfaction asell as their sharing and learning intent (Song et al., 2006; Massey

nd Dawes, 2007). For instance, Jaworski and Kohli (1993) findhat higher destructive conflict is associated with reduced intel-igence dissemination and organizational responsiveness. Masseynd Dawes (2007) also find that dysfunctional conflict is associatedith lower perceived relationship effectiveness. If firms feel bad

owards their partners, the learning pattern, in which one wisheso teach and the other wishes to learn, will deteriorate. Second,estructive conflict impedes knowledge acquisition by distorting

nformation and by alienating partners (Mohr and Spekman, 1994).

his kind of conflict often results in consequences such as distortingnd withholding information, which directly diminish the qualityf the shared information and indirectly bring about feelings ofistrust that alienate the partners, thus making further knowledge

ransfer impossible (Thomas, 1992). Therefore, we suggest:

nagement 29 (2011) 128–142

Hypothesis 2b. Destructive conflict between a manufacturer anda distributor is negatively related to the manufacturer’s knowledgeacquisition.

3.3. Interaction between cooperation and conflict

Inter-organizational relationships constitute a social structureof co-opetition. Simultaneous cooperation and conflict may col-lectively affect the outcomes of knowledge-sharing (Lado et al.,1997). Thus, the association between cooperation and a manufac-turer’s knowledge acquisition may vary with different conditionsof conflict.

Constructive conflict and cooperation are compatible in naturebecause they reflect similar mindsets characterized by high con-cern for both self and others (Tjosvold and Su, 2007). A highdegree of cooperation indicates that more employees and phys-ical assets from each party in a dyadic relationship are groupedtogether to form cross-border teams or to solve problems collec-tively. Since people with different backgrounds and interests areinvolved in this collaboration, a wider variety of ideas about how tobest perform the task might evolve. Cooperative social interactionencourages a partner’s employees to explain the firm’s intentionsand ways of doing things in more specific ways (Solingen et al.,2000) and thereby helps to resolve any misunderstandings andambiguities which emerge in the constructive conflict process.Once the employees fully understand the areas of agreement anddisagreement as well as the underlying reasons, efforts to work outa mutually satisfactory solution become more productive (Rawwaset al., 1997). Therefore, a relationship characterized by both highcooperation and constructive conflict indicates that more peoplewith varied backgrounds and complementary abilities can discusshow a task is performed and can handle it in a healthy way in orderto find compatible solutions. Thus, we suggest:

Hypothesis 3a. The interaction between cooperation andconstructive conflict is complementary to the manufacturer’sknowledge acquisition.

In contrast, destructive conflict and cooperation are fundamen-tally incompatible, in that the mindsets, attitudes and manners arefundamentally different between these two relations (Mohr andSpekman, 1994). The former involves a high concern for self and alow concern for others, whereas the latter emphasizes a high con-cern for both self and others (Jehn, 1997). Thus, if the inter-firmrelationship shows both high cooperation and destructive con-flict, it will probably be unstable and hazardous. In other words,when the level of destructive conflict increases, the positive effectof cooperation will cease to function. Since high cooperation ofteninvolves bringing more employees and equipment together, poten-tial areas for conflict are hard to avoid. If the level of destructiveconflict has increased, the hostile and aggressive situation will beexacerbated. Strong confrontations and harsh words between partymembers may hamper the foundation of cooperation continuity.Meanwhile, destructive conflict may also be interpreted by partnersas a signal of distrust. Because distrust begets distrust (Bradach andEccles, 1989), the cooperation may end up in a vicious cycle of sus-picion and retaliation (Nooteboom et al., 1997), which will decreaseany continued support and knowledge exchange. Therefore, a rela-tionship characterized by both high cooperation and destructiveconflict indicates that more people with varied intentions behaveaggressively and suspiciously when performing collaborative tasks,causing disharmonious relationships which will reduce knowledge

acquisition by the manufacturer. Therefore, we suggest:

Hypothesis 3b. The interaction between cooperation and destruc-tive conflict is detrimental to a manufacturer’s knowledgeacquisition.

Y. Li et al. / Journal of Operations Management 29 (2011) 128–142 133

odel w

3

bspdisoahk

ol1uwitdtMmlemutsa

Hpa

kmacblt

Fig. 2. Conceptual m

.4. The moderating effect of a distributor’s EO

The potential for acquiring market knowledge from co-opetitivealance is further impacted by how much knowledge a particularupply chain relationship can provide. Indeed, consideration of theartner’s EO as an external resource is important in analyzing thisyadic learning relationship, since it is largely the partner’s EO that

mpacts the overall entrepreneurial proclivity and market respon-iveness of the supply chain and reflects different learning valuesf this particular cooperative relation (Li et al., 2008a,b; De Clerqnd Rangarajan, 2008). In fact, a distributor is often chosen for itsigh EO in order to respond to the continuing demand for newnowledge about satisfying consumers’ tastes.

The high EO propensity of distributors represents their seekingf creative solutions, introducing new product and services, and uti-izing new resource combinations for achieving success (Davis et al.,991). The learning potential of market knowledge that the distrib-tor with high EO can offer is greater than that which the distributorith low EO can offer, since a propensity toward entrepreneurship

nspires distributors to be more responsive to emerging trends inhe market (Covin and Slevin, 1991). Therefore, cooperation with aistributor with high EO might better utilize this cooperative rela-ionship in order to acquire knowledge from this particular partner.

eanwhile, a distributor with high EO prefers to cooperate with aanufacturer in a wider range of areas than the distributor with

ow EO does, because the distributor with high EO places greatermphasis on the product differentiation advantage provided by theanufacturer. By transferring more market knowledge to the man-

facturer, the distributor partner can achieve its aim of EO throughhe new products provided by the supply chain collaboration. Inuch a case, cooperation can more efficiently improve knowledgecquisition from the distributors. Therefore, we suggest:

ypothesis 4a. A distributor’s EO positively moderates theositive effect of cooperation on a manufacturer’s knowledgecquisition.

Similarly, the strong EO of the distributor can strengthen thenowledge acquisition achieved by constructive conflict betweenanufacturer and distributor. The distributor with high EO shows

propensity for proactiveness, innovativeness and risk-taking in

oping with market changes (Covin and Slevin, 1991). Therefore,y choosing a distributor partner with high EO, the supply chain

evel EO will increase, thereby leading to the learning potential fromhe constructive conflict process in this supply chain enlarging as

ith full hypotheses.

well. Therefore, working with a distributor with high EO can causethe manufacturer to utilize this constructive conflict relationshipmore efficiently, in order to acquire knowledge from this particularpartner in supply chains.

The following are the key reasons why constructive conflict ismore important for knowledge acquisition when working withhigh EO distributors. First, distributors with high EO may havemore creative suggestions and insights due to their innovativeness(Avlonitis and Salavou, 2007; Renko et al., 2009). The construc-tive conflict process with such partners may lead to more efficientsynergies of ideas, thus providing a better opportunity for themanufacturer to find answers to questions concerning competi-tors. Second, high EO distributors are more proactive in demandingimprovement in the quality and function of existing products thanlow EO distributors are (Handfield et al., 2009), thus providing acertain degree of pressure that forces manufacturers to pay moreattention to finding a better solution by participating in a con-structive conflict process with the distributors. And third, high EOdistributors are more sensitive to market changes (Wiklund, 1999).Thus, in order to quickly respond to current market demand, thedistributors may propose many challenging ideas and tasks to themanufacturers (Morrison et al., 2000). Through participation insuch a constructive conflict process, distributors can gain accessto competitive products, and at the same time manufacturers cangain knowledge from their partners. Thus, the chance to lever-age the constructive conflict process to acquire knowledge will behigher when working with a distributor with high EO than with adistributor with low EO. Therefore, we suggest:

Hypothesis 4b. A distributor’s EO positively moderates the posi-tive effect of constructive conflict on the manufacturer’s knowledgeacquisition.

Conversely, the negative consequences of destructive conflictupon a manufacturer’s knowledge acquisition may be exacer-bated when its distributor partner is characterized by high EO. Onone hand, the learning potential from the high EO of the supplychain may not be able to be leveraged by the destructive con-flict. As indicated by the consequences of destructive conflict, asupply chain characterized by destructive conflict does not per-

form as a knowledge-transferring mechanism, and thus even if thedistributor with high EO might be interested in obtaining new mar-ket knowledge, this knowledge might not be transferred to themanufacturer. On the other hand, when affected by mistrustfulfeelings from destructive conflict, distributors with high EO may

1 ns Ma

lmtdltfi

Haa

s

4

4

4

dqaOnaadstciasi

4

oeer2thomSdsC

tamtrwtq(or

tq

34 Y. Li et al. / Journal of Operatio

ose patience in continuing with this particular manufacturer. Theyay then choose bold and proactive actions to find other partners

o fulfill the needs of consumers. Thus, the chance to leverage theestructive conflict process in order to acquire knowledge will be

ower in working with a distributor with high EO than with a dis-ributor with low EO. Therefore, we suggest the following as ournal hypothesis:

ypothesis 4c. A distributor’s EO positively moderates the neg-tive effect of destructive conflict on a manufacturer’s knowledgecquisition.

The overall conceptual model with all the related hypotheses ishown in Fig. 2.

. Method

.1. Data and samples

.1.1. Pre-testSince the data were collected from the two sides of a

istributor–manufacturer relationship, we designed two paireduestionnaires, for distributor and manufacturer respectively, inccord with the related literature (Anderson and Weitz, 1992;smonbekov et al., 2009). The use of data from paired question-aires as sources of dyadic data is a standard practice in operationsnd marketing management research (e.g., Carter, 2000; Bentonnd Maloni, 2005). We then conducted a pilot test with 16 ran-omly selected distributors and their dyadic manufacturers byemi-structured, in-depth interviews. These experts were askedo review the questionnaire for structure, readability, clarity, andompleteness (Dillman, 1978). As suggested by feedback concern-ng whether the items in the questionnaire were understandablend reflected the actual situation of the supply chain relation-hip, final refinements were made to the phrasing and order of thetems.

.1.2. Data collectionWe chose the Chinese household appliance industry to test

ur research hypotheses. China is an ideal setting, typifying anmerging market because of its huge population, fast-growingconomy, increased liberalization of most economic sectors, andole as a global manufacturing center (Jiang et al., 2007; Liu et al.,009; Zhao et al., 2007). Using sample firms from the same indus-ry helps rule out industry-level differences in dyadic links. Theousehold appliance industry represents one of the most devel-ped and marketized industries in China. It has both world-famousanufacturers (e.g., Haier, Gree, and TCL) and distributors (e.g.,

uning, Gome) and has contributed more than 10% of global pro-uction each year since 1996. Geographically, our survey comprisesample firms nationwide, covering most regions and provinces inhina.

According to the name list of distributors, we mailed 900 ques-ionnaires to distributors who distribute refrigerators, TVs andir-conditioners, with an explanation of the objectives and require-ents of this survey and a promise that we would not give others

he information that their firms provided. In an effort to increase theesponse rate, a modified version of Dillman’s total design methodas followed (Dillman, 1978). Every set of questionnaires involved

hree parts—a copy of the questionnaire, a guide for completing theuestionnaire, and a return envelope. With three-round reminderscalls, travels, e-mails and re-mailing), we received 314 replies,

f which 251 questionnaires were complete and acceptable, for aesponse rate of 27.8%.

We then contacted manufacturers according to the list andelephone numbers provided by these distributors. We sent 251uestionnaires to the designated manufacturers. With the same

nagement 29 (2011) 128–142

follow-up and reminder procedures, we received 246 responses,of which 225 questionnaires were complete and satisfactory, for aresponse rate of 89.6%; the other 21 questionnaires were eliminatedbecause of incomplete information. Thus we obtained 225 pairs ofsamples in total. Appendix A shows the descriptive statistics of dis-tributors and manufacturers concerning their major traits, such asage, size, location, channel history, ownership type and informantprofile.

In both surveys, we recorded responses to the questionnairefrom key informants. The use of key informants as sources of datais standard procedure in operations management (Paulraj et al.,2008). We also took several steps to ensure that the key informantswere sufficiently knowledgeable to respond to the questionnaire.First, 75.3% of distributor informants and 73.6% of manufacturerinformants were senior executives or managers responsible forthe relationship, with the rest being staff members who directlydealt with the cooperative business. The average length of time thatinformants had served in their current positions was 4.7 years fordistributors and 3.5 years for manufacturers. This approach of sur-veying a firm’s executives to study its buyer–supplier relationshipshas been widely adopted in the field of operations management(e.g., Carr and Pearson, 1999; Shin et al., 2000). We also inquiredabout the extent to which the informants were knowledgeableabout the relationship, using a 5-point Likert scale. The mean was4.21 (s.d. = 0.67) for distributors and 4.14 (s.d. = 0.83) for manufac-turers, both of which were satisfactory for analysis.

Non-response bias was tested in two ways. First, the sampleand the population mean of the demographic variables (size, sales,location, ownership and relationship length) were compared tocheck for any significant difference. The t-tests yielded no statisti-cally significant differences (at a 99% confidence interval) betweenthe sample and the population. Additionally, the responses of earlyand late waves of returned surveys were compared to provideadditional evidence of non-response bias (Armstrong and Overton,1977; Lambert and Harrington, 1990). The final sample was splitinto two, depending on the dates the responses were received.Along with the demographic variables, 10 randomly selected vari-ables were included in this analysis. The t-tests performed on thesetwo groups yielded no statistically significant differences (at a 99%confidence interval). These results suggest that non-response biasis not a problem.

In order to minimize social desirability bias, we maintained fullanonymity for all informants throughout the survey process. Wealso followed the measures suggested by Fisher (1993) and usedmore specific and less direct questioning to reduce the social desir-ability bias. In our cover guide, we informed the respondents thatthe survey was designed for research only and that there were noright/wrong answers to our questions.

4.2. Measures

Multi-item scales were used to operationalize all the constructs.A 7-point Likert scale with end points of “strongly disagree” and“strongly agree” was used to measure the items. We used the back-translation method to ensure comparability between items andtheir original formats in English in order to rule out any problemsarising from idiomatic or colloquial wording (Parameswaran andYaprak, 1987).

Following the research of Griffith et al. (2001) and feedbackfrom the field interviews, we measured the manufacturer’s knowl-edge acquisition (MKA) using eight items (Cronbach’s ˛ = 0.932) to

reflect the level of market knowledge which the manufactureracquires from the distributor, such as knowledge about prod-ucts, markets, competitors, market profiles and market shares.Following the research of Rawwas et al. (1997) and Song et al.(2006), we measured constructive conflict (CC) using four items

Y. Li et al. / Journal of Operations Management 29 (2011) 128–142 135

Table 1Means, standard deviations, and correlations.

Variables 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Size 12. Distributor’s life cycle .088 13. Competition turbulence −.265** −.069 14. Technology turbulence −.115 −.061 .502** 15. Rule compliance .164* −.008 −.069 −.222** 16. Hierarchy control .213** .075 −.003 .178** .038 17. Employee pressure taking −.008 −.116 .058 .047 −.059 .216** 18. Service culture −.012 −.096 .191** .093 .212** .260** −.006 19. Cooperation −.104 −.046 .020 −.028 .152* −.131* −.088 −.007 .74110. Constructive conflict .061 .000 .017 .017 −.096 .047 −.045 .080 .168** .74211. Destructive conflict −.056 .037 .019 −.004 .098 −.057 −.083 .070 .384** .128* .80712. Distributor’s EO .346** −.060 −.083 −.099 .228** .360** −.022 .436** −.146* .016 −.085 .73413. Manufacturer’s knowledge acquisition .090 .000 .041 −.040 −.117 .022 .022 .005 .368** .587** .112 −.060 .809

Mean 3.32 3.21 3.60 3.21 5.55 4.52 3.89 5.24 5.10 3.21 5.33 3.97 4.64Standard Deviation 1.418 1.755 2.049 1.755 1.624 1.766 1.888 1.421 1.173 1.561 0.905 1.417 1.328

The data on the diagonal (in bold) is the square root of AVE of the construct.

(ctm˛fciiaA(uiia

ewsfiks21rii2krmwhmtfa(nmdod

* Correlation is significant at the 0.05 level (two-tailed).** Correlation is significant at the 0.01 level (two-tailed).

Cronbach’s ˛ = 0.825) to portray conflicts that bring constructiveonsequences and give benefit to both parties. Again followinghe research of Rawwas et al. (1997) and Song et al. (2006), we

easured destructive conflict (DC) using four items (Cronbach’s= 0.867) to describe conflicts that lead to destructive and harm-

ul consequences. Adapting the research of Luo et al. (2006) aboutross-functional cooperative intensity and feedback from the fieldnterviews, we measured the scale of cooperation (C) using fourtems (Cronbach’s ˛ = 0.828) to portray the mutually cooperativections that bring necessary instruments and manpower together.dapting the research of Atuahene-Gima and Ko (2001) and Li et al.

2006), we measured distributor’s entrepreneurial orientation (DEO)sing five items (Cronbach’s ˛ = 0.792) to portray a distributor’s

nnovativeness, proactiveness and risk-taking. DEO was includedn the distributors’ questionnaires, while all the other constructsre from the manufacturers’ questionnaires.

Because the dependent variables in this study may be influ-nced by other factors outside this model, several control variablesere incorporated into the regression. (1) Firm size refers to the

cale of a firm’s operations (Droge et al., 2003). In general, largerms have greater resources than small firms for assimilatingnowledge (Droge et al., 2003). It was categorized on an ordinalcale with 1: fewer than 51 employees, 2: 51–200 employees, 3:01–500 employees, 4: 501–1000 employees and 5: more than000 employees (Graves and Langowitz, 1993). (2) Perceived envi-onmental turbulence refers to the state of the environment in thendustry, the rate of change in the environment and the firm’s abil-ty or inability to forecast changes in the environment (Song et al.,005). When a firm operates in a highly uncertain environment,nowledge acquisition is critical to help the firm respond to changeapidly and understand how to leverage its capabilities to createaximum value for customers (Sirmon et al., 2007). (3) Mean-hile, the firm’s organizational culture, such as rule compliance,ierarchy control, level of employee stress, and service culture,ay have important implications for knowledge acquisition by

he manufacturer, since the employees of manufacturers with dif-erent cultures may show different behavior in the knowledgecquisition process (Brown and Duguid, 2001; Dodgson, 1993).4) An important control variable from the distributors’ question-

aire – product life cycle – was also included into the regressionodel, since this variable affects knowledge acquisition from the

istributor. The distributor’s leading product was placed withinne of four life cycle stages: introduction, growth, maturity andecline. This was used as a control variable because of its poten-

tial impact on information sharing between channel members(Lee et al., 1997).

4.3. Common method variance

Our use of paired surveys from both distributors and man-ufacturers significantly reduces the possibility of single-side,single-informant common method variance bias. We also tookHarman’s (1967) single factor approach to test this potential prob-lem (Podsakoff and Organ, 1986). According to this test, if commonmethod bias exists, then either (1) a single factor will emerge froma factor analysis of all survey items (Podsakoff and Organ, 1986),or (2) one general factor accounting for most of the common vari-ance existing in the data will emerge (Doty and Glick, 1998). Anun-rotated factor analysis using the Eigen-value-great-than-onecriterion revealed five distinct factors that accounted for 67.3% ofthe variance. The first factor captured only 29.5% of the variancein the data. Since no single factor emerged and the first factor didnot account for most of the variance, we concluded that commonmethod variance is not an issue. Furthermore, a confirmatory factoranalysis (CFA) approach was also used to test for common methodbias (Menon et al., 1996). A model positing that a single factorunderlies the study variables was assessed by linking all items of thedependent and independent factors to a single factor. This modeldid not fit the data and therefore showed that common methodbias was unlikely to be a threat to the findings of this study.

4.4. Reliability and validity

Cumulative normal probability plots demonstrate that each ofthe measures was normally distributed. The correlation matrix,means and standard deviations for the measures that were finallyused are all indicated in Table 1.

Prior to data collection, the content validity of the instrumentwas established by grounding it in existing literature wheneverpossible. As indicated earlier, multi-item scales were developed tomeasure the theoretical constructs. Construct validity was estab-lished using exploratory factor analysis (EFA) and confirmatoryfactor analysis (CFA). As anticipated, all the indicators loaded onto

their underlying constructs during EFA using principal compo-nents method with Varimax rotation. The Eigen-values for thesefactors were above the 1.0 cut-off point (Hair et al., 1998), whilethe percentage of variation was around 67.3% (see Appendix B).The factor loadings were also above the cut-off point of 0.60

136 Y. Li et al. / Journal of Operations Management 29 (2011) 128–142

Table 2Construct measurements.

Construct & Items Cronbach’s ˛ Loading AVE CR

Manufacturer’s knowledge acquisition (MKA)MKA1: Acquired lots of knowledge about substitutive products from this distributor .932 .75 .655 .938MKA2: Acquired lots of knowledge about complementary products from this distributor .85MKA3: Acquired lots of knowledge about consumer behaviors from this distributor .84MKA4: Acquired lots of knowledge about the market shares from this distributor .83MKA5: Acquired lots of knowledge about competitive advantages of our products from this distributor .85MKA6: Acquired lots of knowledge about the market potential from this distributor .87MKA7: Acquired lots of knowledge about marketing issues from this distributor .76MKA8: Acquired lots of knowledge about competitor behaviors from this distributor .84

Cooperation (C)C1: We bring in the equipment or facilities from the partners during our business dealings .828 .71 .549 .829C2: The personnel build close ties with people in other firms .74C3: The cross-firm teams are set up between firms .71C4: We sent the technical and managerial personnel to help the partners .80

Constructive conflict (CC)CC1: We friendly deal with the conflicts encountered .825 .83 .550 .900CC2: The conflict resolving between opinions of this distributor and us is a part of our businesses .78CC3: The conflicts between this distributor and us make the collaboration outcomes more efficient .63CC4: The conflicts between opinions inspire us to find effective solutions .71

Destructive conflict (DC)DC1: The conflicts between this distributor and us have negative impacts on the relationship .867 .60 .652 .880DC2: It is difficult for us to do business with this distributor because of the serious conflict .93DC3: The distributor obstructs us from the pursuit of our interest .88DC4: There exists personal conflict between our employees and distributor’s employees .78

Distributor’s EO (DEO) (From Distributor’s questionnaire)DEO1: Take new ways of action that is different from the competitors .792 .90 .539 .852DEO2: Incline to create a new competition environment in order to sustain our development .76DEO3: Take bold and proactive actions when faced with uncertain environments .67DEO4: Seize the opportunity first, and then find the related resources and capabilities .64

N cted.

(e(sfiafiiaaTa

mTcifebiwsicactstTv

DEO5: Emphasize on the introducing of new product

otes: CR refers to composite reliability, while AVE refers to average variance extra

Hair et al., 1998). A CFA measurement model was used to furtherstablish construct validity. The values for the model-fit indicesCFI = 0.98, NNFI = 0.98, NFI = 0.96, RFI = 0.96, RMSEA = 0.07, and chiquare/degree of freedom = 2.29) show that there is a sufficientt between the hypothesized model and the observed data (Hund Bentler, 1999; Bagozzi and Yi, 1988). The standardized coef-cients and t-values for the individual paths show that all the

ndicators are significantly related to their underlying constructsnd hence exhibit convergent validity. In addition, the average vari-nce extracted (AVE) values for all constructs exceed 0.539 (seeable 2), which, being greater than 0.50 (Fornell and Larcker, 1981),lso indicates convergent validity.

Discriminant validity was checked using CFA. Measurementodels were constructed for all possible pairs of the constructs.

hese models were tested on each selected pair by first allowing fororrelation between the two constructs to be free and then fixingt at 1.0. A significant difference in chi-square values for fixed andree solutions indicates distinctiveness of two constructs (Bagozzit al., 1991). The results in this instance show that all the differencesetween the fixed and free solutions are significant, thus provid-

ng strong evidence of discriminant validity. As an alternative test,e compared the correlation between two latent constructs to the

quare root of AVE estimates (Fornell and Larcker, 1981). Accord-ng to this test, discriminant validity exists if the items share moreommon variance with their respective construct than any vari-nce the construct shares with the other constructs. Therefore, theorrelation between each pair of constructs should be less than

he square root of AVE for each individual construct. By compari-on, we can conclude that none of the correlations is higher thanhe square root of AVE for each individual construct (see Table 1).hese results collectively provide strong evidence of discriminantalidity.

.67

Reliability was assessed using the internal consistency methodvia Cronbach’s alpha (Cronbach, 1951; Nunnally, 1978). Typically,reliability coefficients of 0.70 or higher are considered adequate(Cronbach, 1951; Nunnally, 1978). All constructs had a Cronbach’salpha greater than 0.792 (see Table 2), thus showing the reliabilityof all the theoretical constructs. Alternatively, following Bagozziand Yi (1988), we computed composite reliability (CR) scores toassess construct reliability. According to these authors, a CR valuegreater than 0.70 implies that the variance captured by the fac-tor is significantly more than the variance indicated by the errorcomponents. As reported in Table 2, all factors have CRs greaterthan 0.829. Taken together, the results from the instrument devel-opment process show that the theoretical constructs exhibit goodpsychometric properties.

4.5. Regression results

Our hypotheses were tested using hierarchical regressionanalysis, where the dependent variable was the manufacturer’sknowledge acquisition (MKA). We should note here that, beforeconducting any regression analysis, we checked our data for viola-tions of normality assumptions, outliers, and any other problems.We found no significant violations and concluded that the datawere amenable to regression. We averaged all items belongingto each construct to obtain overall construct values. In order toguard against multi-collinearity problems, we standardized all

the independent, moderating and dependent variables in theregression models as suggested by Aiken and West (1991) andJaccard et al. (1990).

Following the recommendations of Cohen (2003), the variableswere entered into the model in sequential steps: control variables,

Y. Li et al. / Journal of Operations Management 29 (2011) 128–142 137

Table 3Regression models: Predictors of the manufacturer’s knowledge acquisition (N = 225).

Model 1 Model 2 Model 3 Model 4 Model 5

ControlsSize .101 .162** .143** .248*** .183***

Competition turbulence .243*** .288*** .205*** .190*** .183***

Technology turbulence −.263*** −.293*** −.222*** −.217*** −.303***

Rule compliance .021 −.133* .088 −.182*** .084Hierarchy control .120* .125* .112* −.040 .218***

Employee pressure taking .206*** .200*** .171*** .126** .106**

Service culture .070 .093 −.152* .100* .161***

Distributor’s product life cycle −.012 .073 .080 .203*** .151**

PredictorsCooperation (C) .399*** .380*** .415*** .387***

Constructive conflict (CC) .382*** .203*** .257***

Destructive conflict (DC) −.181*** −.186*** −.237***

C × CC −.517*** −.430***

C × DC −.145*** −.164***

Distributor’s EO (DEO) −.355***

DEO × C .118*

DEO × CC .095*

DEO × DC −.096*

Regression ResultsR2 .128 .272 .432 .552 .612Adjusted R2 .047 .157 .323 .442 .481F Value 1.569+ 2.364*** 3.951*** 5.022*** 4.673***

The regression coefficients are reported as beta values.+ p < 0.1.

mT

vewiitt

deifettaHirar

tRis3p

lpMfi

* p < 0.05.** p < 0.01.

*** p < 0.001.

ain effect variables, interaction items and moderating variables.he results of each step are shown in Table 3.

Model 1 is the base model that includes only control variables (Falue = 1.569, p < 0.1). In Model 2, the independent variable of coop-ration was entered into the regression equation, and the equationas significant (F value = 2.364, p < 0.001). The adjusted R2 value

ncreased significantly from Model 1 (0.047) to Model 2 (0.157),ndicating a significant effect of cooperation. The result suggestshat cooperation is positively related to MKA (ˇ = 0.399, p < 0.001),hus supporting Hypothesis 1.

In Model 3 (which was newly added), the other two indepen-ent variables of constructive conflict and destruct conflict werentered into the regression equation, and the equation was signif-cant (F value = 3.951, p < 0.001). The adjusted R2 value increasedrom Model 2 (0.157) to Model 3 (0.323), indicating a significantffect of both types of conflict. The result suggests that construc-ive conflict is positively related to MKA (ˇ = 0.382, p < 0.001),hus supporting Hypothesis 2a, while destructive conflict is neg-tively related to MKA (ˇ = −0.181, p < 0.001), thus supportingypothesis 2b. No higher order effects were found to be signif-

cant for cooperation, constructive conflict and destruct conflictespectively, indicating that these co-opetition relations affect

manufacturer’s acquisition of market knowledge in a linearelationship.

Next, the interaction item was entered into the equation, andhe model was significant (F value = 5.022, p < 0.001). The adjusted2 value increased from Model 3 (0.323) to Model 4 (0.442), indicat-

ng the interaction effects. The coefficient of C × CC is negative andignificant (ˇ = −0.517, p < 0.001), thus not supporting Hypothesisa. The coefficient of C × DC is negative and significant (ˇ = −0.145,< 0.001), thus supporting Hypothesis 3b.

In the final step, the moderating effects of DEO were ana-yzed, and the overall model was significant (F value = 4.673,< 0.001). The adjusted R2 value increased from Model 4 (0.442) toodel 5 (0.481), thus indicating the moderating effects. The coef-

cient of DEO × C is positive and significant (ˇ = 0.118, p < 0.05),

and the coefficient of DEO × CC is also positive and significant(ˇ = 0.095, p < 0.05), while the coefficient of DEO × CC is negativeand significant (ˇ = −0.096, p < 0.05). Thus, Hypotheses 4a–4c aresupported.

To check the robustness of the regression results, we conductedan additional analysis by using the weighted-average method to re-calculate the construct values (DiStefano et al., 2009). We weightedeach item based on factor scores to come up with an overall valuefor the construct. By comparing the new results from this weighted-average method and the original results, we find that there are nosignificant changes due to changes in weightings in the regressionmodel. Therefore, we conclude that the related hypotheses in ourresults are indeed supported by our samples.

5. Discussion

5.1. Theoretical implications

This study provides an explanation of the relationships amongcooperation, constructive vs. destructive conflict, distributor’s EO,and manufacturer’s knowledge acquisition (MKA), and empiricallyexamines the conceptual model in the Fig. 2. Besides the generalrecognition that relations between a manufacturer and a distribu-tor in a supply chain will tend to become co-opetitive, questionsabout the effects of different combinations between cooperationand constructive vs. destructive conflicts have become importantissues in strategic knowledge management in a supply chain (e.g.,Webster, 1995; Kumar and Dissel, 1996). Meanwhile, by explor-ing entrepreneurial issues in a supply chain learning process, thisstudy also provides new contributions to the intersection of sup-ply chain management and entrepreneurship literature through

analyzing the moderating effect of the partners’ EO on the relation-ship between co-opetitive relations and manufacturer’s knowledgeacquisition.

The first set of findings of this study highlight the importance ofthe co-opetition perspective in supply chain knowledge manage-

1 ns Ma

mtat

mathp(wo

kai

eiratteiee

tTcsibpb(stiibcedbsc

mtTtra(wmtrebeer

38 Y. Li et al. / Journal of Operatio

ent. From the co-opetition perspective, we examine the effectshat co-opetition behavior by a manufacturer has on its knowledgecquisition in a supply chain, and find new results which extendhe current operations management literature.

Our first finding, that cooperation is positively related to theanufacturer’s knowledge acquisition, shows that cooperative

ctivity does indeed act as a key factor in overcoming knowledgeransfer barriers, by creating an interdependent, trustful, mutuallyelpful and communication-intensive atmosphere between sup-ly chain partners. This result supports the assertion of Inkpen1998), who argues that inter-firm collaboration provides firmsith a unique opportunity to leverage their strengths with the help

f partners.We also find that, unlike constructive conflict which promotes

nowledge acquisition by brainstorming and better understandingpartner’s intentions and capabilities, destructive conflict inhibits

t because of deteriorated relations and reduced social interactions.These two results extend conflict management literature (Ayoko

t al., 2002; Mohr and Spekman, 1994; Song et al., 2006) by analyz-ng the conflict issue in a cross-boundary learning process. Theseesults also provide support to the research of Rawwas et al. (1997)nd Jehn (1997), who emphasize the difference between construc-ive and destructive conflict and their dissimilar roles in influencinghe parties’ behavior and relational performance. Thus, both coop-ration and conflict play unique roles for the knowledge acquisitionssue in the supply chain cooperation. From these results, this studyxplains the effects of different co-opetition factors on the knowl-dge acquisition.

We also examine the interactive effects of cooperation andwo types of conflict on a manufacturer’s knowledge acquisition.he results show that the destructive conflict indeed works withooperation in a detrimental way, which confirms our hypothe-is. However, an unexpected result emerged with respect to thenteraction effect between cooperation and constructive conflicteing negative instead of positive. The possible reason for this unex-ected result may be related to the fact that cooperation behavioretween channel members leads to improvement of guanxi in ChinaLeung et al., 2005), and the guanxi itself may constrain the con-tructive conflict (e.g., discussions) since Chinese people may thinkhe importance of saving face between acquaintances (a key issuen keeping the guanxi) is stronger than the importance of find-ng answers through debating (Tjosvold and Su, 2007). Therefore,y empirically examining the interactive effect of cooperation andonflict in the area of supply chain management, our study extendsxisting co-opetition literature, which has paid attention to how theifferent co-opetition factors individually affect firm performanceut has ignored their interactive effects. Our study also leads to theuggestion that further research should be done on the possibleultural impacts in this interesting area.

The second set of findings of our study highlight the importantoderating effects of a partner’s entrepreneurial orientation on

he relationships between co-opetition and knowledge acquisition.hese findings extend the current literature relating to contex-ual analysis of operations management. Although researchers haveecognized that the relationship between OM issues and cooper-tive outcomes should be contingent on some contextual factorsArgote et al., 2003; Burton et al., 2002), there is still considerableork left to be done (Giunipero et al., 2008). By examining theoderating effects of the distributor’s EO, this study responds to

he call by Argote et al. (2003) for more contextual analysis on theelationship between properties of dyadic relationships and knowl-

dge management with intersectional perspectives, and the cally Sarkar et al. (2001) for analyzing supply chain issues with anntrepreneurship lens, as well as the call by Bhuian et al. (2005) forxamining the possible impact of EO on the performance of channelelationship management.

nagement 29 (2011) 128–142

Meanwhile, by examining the distributor’s EO as the modera-tor, we view this study as an important extension in the emergingstream of research on the strategic supply chain management(Hult et al., 2007)—strategic, operational and technological integra-tion of supply chain participants through relationships, processesand information-sharing to provide member organizations with acompetitive advantage (Hult et al., 2004; Upson et al., 2007). Ourfindings help explain why some manufacturers outperform oth-ers in terms of more valuable and timely knowledge acquisition,by highlighting the joint consideration of operational (maintainingthe co-opetition balance between channel members) and strate-gic issues (finding a distributor partner with high entrepreneurialorientation).

Moreover, from the entrepreneurship perspective, by exam-ining the distributor’s EO as a moderator, our findings extendexisting entrepreneurship literature from a focus on the endoge-nous effect of a firm’s own EO to a focus on the exogenous effectof a partner’s EO. Existing entrepreneurship literature has providedmuch evidence about why the firm’s entrepreneurship is critical fororganizational learning and value creation within firms or withincollaborations (e.g., Ketchen and Hult, 2007; Zhou et al., 2005;Wiklund and Shepherd, 2005). Our study contributes to this area byhighlighting the criticality of also considering the exogenous effectof supply chain partner’s EO. Our findings are supported by field-work which reveals that firms are discriminating in their choiceof whom to form a partnership with and seeking out those whooffer the highest expected returns by showing unique character-istics (e.g., high entrepreneurial orientation). Thus, these resultsabout how a partner’s EO influences the efficiency of co-opetitiverelation management in the knowledge acquisition process extendsentrepreneurship literature from intra-organization analysis tointer-organization (supply chain level) analysis, and highlights theneed to consider the EO issue not only from the perspective ofthe firm itself and its direct impact on the performance, but alsofrom the perspective of the partner and its indirect or moderatingimpacts on operations management issues.

Furthermore, our results show that strong complementary rela-tionships exist between a distributor’s EO and the co-opetitionbehavior of a manufacturer, indicating that the co-opetition behav-ior of a manufacturer and a partner’s EO can formulate thecomplementary assets in supply chain cooperation to improveknowledge acquisition. Thus, this paper opens a potential doorfor outstanding entrepreneurship and operations managementscholars to advance novel and path-breaking ideas that have thepotential to further contribute to both fields and inform our under-standing of wealth creation in organizations and in supply chainsas a whole.

5.2. Managerial implications

Besides its theoretical contributions to the literature, thispaper’s empirical findings provide the following managerial impli-cations. First, the co-existence of cooperation and conflict, and thedifferent interaction effects of constructive vs. destructive conflictand cooperation, indicate that a manufacturer, as the recipientof knowledge, should actively create functional supply chain co-opetitive activities. Even in a business context such as in China, witha long history of conflict avoidance (Ding, 1998; Tse et al., 1994), thebeneficial role of constructive conflict should be emphasized andencouraged. We indicate that Chinese managers in manufacturingcompanies can use the constructive debate approach in discussing

their different opinions and forging productive partnerships withtheir distributor partners.

Second, the yin-yang nature of a co-opetitive supply chainrelationship challenges traditional Western notions of inter-firmrelational management in which relations are controlled and

ns Ma

deaidcctattssf

ttoaimtEEtn

mmboebimarpsabbtoama2Mecttnttfipita

5

s

Y. Li et al. / Journal of Operatio

irected by a dominant player and characterized by either a coop-rative or a conflictive atmosphere. It has been recognized thatmanufacturer’s competitive advantage may rest on tacit, inim-

table collaborative and conflictive balance relationships with itsistributor partners. We believe that the manufacturer’s relationalapability of balancing co-opetition well can result in a sustainedompetitive advantage because the manufacturer can fully exploithe collaboration opportunities to acquire partner knowledge,nd thereby in turn can increase its market responsiveness andhe ability to meet new customer demands. Thus, the manufac-urer in a manufacturer–distributor supply chain should build andtrengthen this relational capability of balancing co-opetition andhould leverage these skills to enhance its knowledge acquisitionrom distributor partners.

Third, managers from manufacturing firms should recognizehat strong EO in a distributor partner is very important in ordero improve the efficiency of knowledge acquisition through co-petition relations. It is not feasible for a firm to work closely withll the firms in a supply chain, because not every firm is equally crit-cal to value creation. Moreover, co-opetitive relations are costly to

aintain. Thus, each partner must be selective in managing rela-ionships with a limited set of partners, such as the ones with highO. Manufacturers should choose distributors with a high level ofO and should continuously help these distributors to strengthenheir EO in order to enhance supply chain-level market responsive-ess.

Fourth, the findings suggest that interfirm dynamics in aanufacturer–distributor supply chain in China can indeed takeany forms of co-opetition interplays, and that different com-

inations of cooperation and conflict have different impactsn the manufacturer’s knowledge acquisition. Meanwhile, thentrepreneurial situation in China may complicate the potential fitetween different co-opetitive strategies and supply chain learn-

ng circumstances. In order to succeed in this highly competitivearket, a manufacturer should work with a distributor who hashigh level of EO externally and should manage the co-opetition

elation internally to fully acquire knowledge from the supply chainartnership. Our results suggest that Chinese manufacturers shouldelect distributors with strong EO as partners in a supply chainnd cooperate with them to probe market opportunities. As Chinaecomes the manufacturing factory of the world, the competitionetween manufacturers will intensify. Thus, in order to achievehe aim of industrial upgrading and transformation of the modef growth, manufacturers need to provide fast responsiveness asunique market opportunity (Langerak, 2001). In fact, China’sanufacturing industry has formed a certain level of competitive

dvantage through improving efficiency and cost savings (Li et al.,008a,b; Zhu and Sarkis, 2004; Ianchovichina and Martin, 2004).eanwhile, many distributors with strong entrepreneurship have

merged in China in recent years. Their existence, on the one hand,reates a higher demand for the manufacturer to cope with, and onhe other hand creates a valuable opportunity for the manufacturero improve acquisition of their market information. Therefore, theew trend of jointly considering entrepreneurship in the distribu-or and the co-opetition management of the manufacturer may leado a new way of upgrading the Chinese manufacturing industry. Ourndings suggest that manufacturers should view their distributorartners’ entrepreneurial orientation as a key criterion for select-

ng the right partners, and engage in co-opetition with distributorso enhance the market responsiveness by improving knowledgecquisition from these partners.

.3. Limitation and future directions

Although this study provides several new insights into under-tanding interfirm co-opetition relations and a manufacturer’s

nagement 29 (2011) 128–142 139

knowledge acquisition, it is subject to some limitations. First, onelimitation lies in the unique research context of the study, China.As with most research, generalization beyond the sample framemust be undertaken with care. The findings may be limited to theinstitutional and business culture context of China, since it couldbe argued that different relationships between co-opetition andknowledge acquisition might exist in alternative contexts. Differentcountries have different business cultures and institutional con-texts that may affect a manager’s decision-making and perceptionsof the partner’s cooperative or conflict behaviors. Future effortsshould extend similar inquiries to other nation/district settings, andfurthermore should include national-level factors such as economicdevelopment, legal system, social norms, and political regime in anintegrated analysis. As such, the extension of this basic model to amulti-country or multi-area context would substantially enhancethe understanding of the issues addressed here at a broader level.

Second, this study derives results from its cross-sectionaldesign, which means causality cannot be established. Thus,these relationships should be examined longitudinally. Explor-ing these issues longitudinally would also provide additionalinsights into the underlying model that proposed. It would beinteresting to examine how cross-boundary co-opetition relationsmay evolve over time into creating a more effective learningenvironment. Overall, the notion of the dynamics of interfirmco-opetition may provide future research agenda with a novelway of thinking about the complexities of supply chain relationmanagement.

Third, besides the interaction and moderating analysis of thisco-opetition relationship, an inquiry into the antecedents of dif-ferent co-opetition combinations might also be an interestingresearch topic. For example, some antecedents (such as mediatedversus non-mediated power or different conflict-handling strate-gies) may influence whether the conflicts will be either constructiveor destructive. Future studies should seek to identify additionaldrivers of co-opetition and to examine their impacts in this inter-firm interaction process.

6. Conclusion

To date little has been known about how co-opetition behav-ior affects a manufacturer’s knowledge acquisition, and still lessabout how a partner’s EO moderates these relationships. This studycontributes to this area by examining the individual and inter-active influence of cooperation and conflicts on a manufacturer’sknowledge acquisition under the circumstance of distributors withdifferent EO. The results indicate that the cooperation and two typesof conflict play both individual and interactive effects on the man-ufacturer’s knowledge acquisition, thus providing evidence for theimportance of the co-opetition perspective in supply chain knowl-edge management. The findings also indicate that the distributor’sEO positively moderates the co-opetition–knowledge acquisitionrelationship, thus highlighting the importance of analyzing theimpact of entrepreneurship in supply chains. In summary, it isthe first attempt in this area that deals with how to manage co-opetition relations with particular partners with different EO inorder to promote the manufacturer’s knowledge acquisition in sup-ply chains.

Acknowledgements

We thank the Editor and our special issue associate editorJayanth Jayaram and two anonymous reviewers for excellent edi-torial guidance and comments and to China’s Ministry of Education(09JZD0030) and National Natural Science Foundation (70872090)for their research support.

1 ns Ma

A

Ar

40 Y. Li et al. / Journal of Operatio

ppendix A. Profile of matched survey sample

Characteristics of sampleand respondents

Distributor Manufacturer

1. Company age 8.1 years 12.2 years2. Length of the

buyer–supplierrelationship

5.8 years 5.8 years

3. LocationNorthern China 20.2% 16.2%Central China 18.5% 14.5%Eastern China 14.3% 22.3%Southern China 21.4% 25.4%Northwestern China 13.0% 11.0%Southwestern China 12.6% 10.6%

4. Size of employees≤200 31.8% 26.9%201–500 23.9% 32.9%More than 500 44.3% 40.2%

5. Company sales (in million RMB)≤10 25.0% 15.0%10–50 30.0% 35.0%50–200 21.0% 27.0%More than 200 17.5% 18.5%Unreported 6.5% 4.5%

6. Type of firm ownershipState-owner enterprises 11.5% 28.6%Joint ventures 5.9% 8.9%Limited companies 43.9% 37.6%Private companies 7.6% 13.8%Collective enterprises 19% 8.6%Others (village firms,etc.)

12.1% 2.5%

7. Industry typeRefrigerator 29.9% 32.4%TV 35.5% 38.7%Air-condition 34.6% 28.9%

8. Job position of the respondentPresident/CEO 38.1% 37.9%Purchasing/salesmanager

21.1% 20.8%

General manager 15.3% 14.9%Others 25.5% 26.4%

9. Tenure of the respondentin current position

4.7 years 3.5 years

10. Length of therespondent involving inthe focal relationship

3.8 years 2.5 years

ppendix B. Exploratory factor analysis (EFA) with Varimaxotation

Constructs & Items Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Manufacturer’s knowledge acquisition (MKA)MKA1 .744 .150 .002 .150 .068MKA2 .846 .066 −.039 .078 .119MKA3 .837 −.045 −.037 .003 .207MKA4 .837 −.140 .011 .057 .200MKA5 .857 .027 .002 .040 .197MKA6 .750 .084 −.054 .262 .281MKA7 .715 −.028 −.033 .313 .337MKA8 .682 .095 −.044 .225 .242

Destructive conflict (DC)DC1 −.030 .668 −.090 .162 .266

DC2 −.008 .914 −.016 .121 .042DC3 .025 .890 −.017 .116 .013DC4 .127 .822 −.031 .193 −.109

Distributor’s EO (DEO)DEO1 −.012 −.055 .862 −.049 −.024DEO2 −.123 −.088 .782 −.002 −.046DEO3 −.014 .017 .696 −.062 .054

nagement 29 (2011) 128–142

Appendix B (Continued )Constructs & Items Factor 1Factor 2Factor 3Factor 4Factor 5

DEO4 −.047 −.094 .678 −.084 .074DEO5 .080 .066 .697 −.026 −.022

Constructive conflict (CC)CC1 .166 .144 −.141 .724 .196CC2 .159 .326 −.063 .720 −.007CC3 .102 .054 −.035 .826 −.064CC4 .218 .161 −.034 .800 .043

Cooperation (C)C1 .364 −.031 −.005 −.081 .772C2 .350 .168 −.039 −.026 .730C3 .204 .044 .011 .105 .736C4 .304 .012 .109 .107 .718

ResultsEigenvalue 5.48 3.02 2.84 2.75 2.71Percentage of variance explained 21.94 12.11 11.37 11.00 10.87Cumulative % of variance explained21.94 34.05 45.42 56.42 67.29

References

Aiken, L.S., West, S.G., 1991. Multiple Regression: Testing and Interpreting Interac-tions. Sage Publications, Newbury Park, CA.

Albino, V., Carbonara, N., Giannoccaro, I., 2007. Supply chain cooperation in indus-trial districts: a simulation analysis. European Journal of Operational Research177, 261–280.

Ambler, T., Styles, C., Xiucun, W., 1999. The effect of channel relationships and guanxion the performance of inter-province export ventures in the People’s Republicof China. International Journal of Research in Marketing 16 (1), 75–87.

Anderson, E., Weitz, B., 1992. The use of pledges to build and sustain commitmentin distribution channels. Journal of Marketing Research 29 (1), 18–34.

Anderson, J.C., Narus, J.A., 1990. A model of distributor firm and manufacturer firmworking partnerships. Journal of Marketing 54 (1), 42–58.

Arend, R.J., Wisner, J.D., 2005. Small business and supply chain management: Is therea fit? Journal of Business Venturing 20 (3), 403–436.

Argote, L., McEvily, B., Reagans, R., 2003. Managing knowledge in organizations: anintegrative framework and review of emerging themes. Management Science49 (4), 571–582.

Argyle, M., 1991. Cooperation: The Basis of Sociability. Routledge, New York.Armstrong, J.S., Overton, T.S., 1977. Estimating nonresponse bias in mail surveys.

Journal of Marketing Research 13 (3), 396–402.Atuahene-Gima, K., Ko, A., 2001. An empirical investigation of the effect of market

orientation and entrepreneurship orientation alignment on product innovation.Organization Science 12 (1), 54–74.

Avlonitis, G.J., Salavou, H.E., 2007. Entrepreneurial orientation of SMEs, prod-uct innovativeness, and performance. Journal of Business Research 60 (5),566–575.

Ayoko, O.B, Hartel, C.E.J., Callan, V.J., 2002. Resolving the puzzle of productive anddestructive conflict in culturally heterogeneous workgroups: a communicationaccommodation theory approach. International Journal of Conflict management13 (2), 165–195.

Bagozzi, R.P., Yi, Y., 1988. On the evaluation of structural equation models. Academyof Marketing Science 16 (1), 74–94.

Bagozzi, R.P., Youjae, Y., Phillips, L.W., 1991. Assessing construct validity in organi-zational research. Administrative Science Quarterly 36 (3), 421–458.

Bengtsson, M., Kock, S., 2000. Co-opetition in business networks—To cooperate andcompete simultaneously. Industrial Marketing Management 29, 411–426.

Benton, W.C., Maloni, M., 2005. The influence of power driven buyer/seller relation-ships on supply chain satisfaction. Journal of Operations Management 23 (1),1–22.

Bhuian, S.N., Menguc, B., Bell, S.J., 2005. Just entrepreneurial enough: the moderatingeffect of entrepreneurship on the relationship between market orientation andperformance. Journal of Business Research 58 (1), 9–17.

Boyer, K.K., Lewis, M.W., 2002. Competitive priorities: Investigating the need for sup-ply chain trade-offs in operations strategy. Journal of Operations Management11 (1), 9–20.

Bradach, J.L., Eccles, R.G., 1989. Price, authority and trust: from ideal types to pluralforms. Annual Review of Sociology 15, 97–118.

Brandenburger, A.M., Nalebuff, B.J., 1996. Co-opetition: A Revolutionary Mindsetthat Combines Competition and Cooperation in the Marketplace. Harvard Busi-ness School Press, Boston.

Brown, J.S., Duguid, P., 2001. Knowledge and Organization: A Social-practice Per-spective. Organization Science 12 (2), 198–213.

Burkink, T., 2002. Cooperative and voluntary wholesale groups: Channel coor-

dination and interfirm knowledge transfer. Supply Chain Management: AnInternational Journal 7 (2), 60–70.

Burton, R.M., Lauridsen, J., Obel, B., 2002. Return on assets loss from situational andcontingency misfits. Management Science 48, 1461–1485.

Carr, A.S., Pearson, J.N., 1999. Strategically managed buyer-supplier relationshipsand performance outcomes. Journal of Operations Management 17, 497–519.

ns Ma

C

C

C

C

C

C

D

D

D

D

D

D

D

D

D

D

D

D

D

E

E

E

E

F

F

F

F

G

G

G

G

G

G

H

Y. Li et al. / Journal of Operatio

arter, C.R., 2000. Ethical issues in international buyer-supplier relationships: adyadic examination. Journal of Operations Management 18, 191–208.

hen, M.J., 2002. Transcending paradox: the Chinese “middle way” perspective. AsiaPacific Journal of Management 19, 179–199.

hen, M.J., 2008. Reconceptualizing the competition-cooperation relation-ship: a transparadox perspective. Journal of Management Inquiry 17 (4),288–304.

ohen, J., 2003. Applied Multiple Regression/Correlation Analysis for the BehavioralSciences. Lawrence Erlbaum Associates, Hillsdale, NJ.

ovin, J.G., Slevin, D.P., 1991. A conceptual model of entrepreneurship as firm behav-ior. Entrepreneurship Theory and Practice 16 (1), 7–25.

ronbach, L.J., 1951. Coefficient alpha and the internal structure of tests. Psychome-trika, 297–334.

as, A., 2003. Knowledge and productivity in technical support work. ManagementScience 49 (4), 416–431.

as, T., Teng, B., 2002. The dynamics of alliance conditions in the alliance develop-ment process. Journal of Management Studies 39 (5), 725–746.

avis, D., Morris, M., Allen, J., 1991. Perceived environmental turbulence and itseffect on selected entrepreneurship, marketing, and organizational character-istics in industrial firms. Journal of the Academy of Marketing Science 19 (1),43–51.

e Clercq, D., Dimov, D., Thnogpapanl, N., 2010. The moderating impact of inter-nal social exchange processes on the entrepreneurial orientation–performancerelationship. Journal of Business Venturing 25 (1), 87–103.

e Clerq, D., Rangarajan, D., 2008. The role of perceived relational support inentrepreneur–customer dyads. Entrepreneurship Theory and Practice 32 (4),659–683.

ess, G.G., Lumpkin, G.T., McFarlin, D., 2005. The role of entrepreneurial orientationin stimulating effective corporate entrepreneurship. Academy of ManagementExecutive 19 (1), 147–156.

illman, D.A., 1978. Mail and Telephone Surveys: The Total Design Method. JohnWiley and Sons, New York.

ing, D., 1998. In Search of Determinants of Chinese Conflict Management Stylesin Joint Ventures: An Integrated Approach. City University of Hong Kong, HongKong.

iStefano, C., Zhu, M., Mindrila, D., 2009. Understanding and using factor scores:considerations for the applied researcher. Practical Assessment, Research & Eval-uation 14 (20), 1–11.

odgson, M., 1993. Organizational learning: a review of some literatures. Organiza-tion Studies 14, 375–394.

oty, D.H., Glick, W.H., 1998. Common method bias: does common methods vari-ance really bias results? Organizational Research Methods 1 (4), 374–406.

roge, C., Claycomb, C., Germain, R., 2003. Does knowledge mediate the effect of con-text on performance? Some initial evidence. Decision Sciences 34 (3), 541–568.

roge, C., Jayaram, J., Vickery, S., 2000. The ability to minimize the timing of newproduct development and introduction: An examination of antecedent factors inthe North American automobile supplier industry. Journal of Product InnovationManagement 17, 24–40.

ckert, J.A., Rinehart, L.M., 2005. Constructive conflict outcomes: Conceptualiza-tion, measurement and initial validity. Marketing Management Journal 15 (2),144–157.

liashberg, J., Michie, D.A., 1984. Multiple business goal sets as determinants of mar-keting channel conflict: An empirical study. Journal of Marketing Research 21,75–88.

riksson, P.E., 2008. Achieving suitable co-opetition in buyer–supplier relation-ship: the case of AstraZeneca. Journal of Business to Business Marketing 15 (4),425–454.

vangelista, F., Hau, L.N., 2009. Organizational context and knowledge acquisitionin IJVs: an empirical study. Journal of World Business 44 (1), 63–73.

isher, R.J., 1993. Social desirability bias and the validity of indirect questioning.Journal of Consumer Research 20, 303–315.

lynn, B.B., Huo, B., Zhao, X., 2010. The impact of supply chain integration on per-formance: a contingency and configuration approach. Journal of OperationsManagement 28 (1), 58–71.

lynn, B.B., Zhao, X., Roth, A., 2007. The myth of the dragon: operations managementin today’s China. Business Horizons 50 (3), 177–183.

ornell, C., Larcker, D.F., 1981. Evaluating structural equations models with unob-servable variables and measurement error. Journal of Marketing Research 18,39–50.

iunipero, L.C., Denslow, D., Eltantawy, R., 2005. Purchasing/supply chain manage-ment flexibility: moving to an entrepreneurial skill set. Industrial MarketingManagement 34 (6), 602–613.

iunipero, L.C., Hooker, R.E., Matthews, S.J., Yoon, T.E., Brudvig, S., 2008. A decadeof SCM literature: past, present and future implications. Journal of Supply ChainManagement 44 (4), 66–86.

nyawali, D.R., He, J., Madhavan, R., 2006. Impact of co-opetition on firm competitivebehavior: an empirical examination. Journal of Management 32 (4), 507–530.

rant, R.M., 1996. Toward a knowledge-based theory of the firm. Strategic Manage-ment Journal 17, 109–122.

raves, S.B., Langowitz, N.S., 1993. Innovative productivity and returns to scale in

the pharmaceutical industry. Strategic Management Journal 14 (8), 593–605.

riffith, D.A., Zeybek, A.Y., O’Brien, M., 2001. Knowledge transfer as a means forrelationship development: a Kazakhstan-foreign international joint ventureillustration. Journal of International Marketing 9 (2), 1–18.

air, J., Anderson, J.R., Tatham, R., 1998. Multivariate Data Analysis. Prentice-Prentice, Upper Saddle River, NJ.

nagement 29 (2011) 128–142 141

Handfield, R., Peterson, K., Cousins, P., Lawson, B., 2009. An organizationalentrepreneurship model of supply management integration and performanceoutcomes. International Journal of Operations & Production Management 29(2), 100–126.

Hardy, B., 2009. Growing significance of communities and collaboration in discoveryand development. Future Medicinal Chemistry 1 (3), 435–449.

Harman, H., 1967. Modern Factor Analysis. University of Chicago, Chicago.Herrgard, T.H., 2000. Difficulties in diffusion of tacit knowledge in organizations.

Journal of Intellectual Capital 1 (4), 357–365.Hitt, M.A., Ireland, R.D., Camp, S.M., Sexton, D.L., 2001. Entrepreneurial strategies for

wealth creation. Strategic Management Journal 22, 479–491.Hofestede, G., Bond, M.H., 1988. The Confucius connection: from cultural roots to

economic growth. Organizational Dynamics 16, 4–21.Hoffman, L.R., Harburg, E., Maier, N.R.F., 1962. Differences and disagreement as

factors in creative group problem solving. Journal of Abnormal and Social Psy-chology 64, 206–214.

Hu, L., Bentler, P.M., 1999. Cutoff criteria for fit indexes in covariance structure anal-ysis: conventional criteria versus new alternatives. Structural Equation Model 6(1), 1–55.

Hult, G.T.M., Ketchen, D.J., Arrfelt, M., 2007. Strategic supply chain management:improving performance through a culture of competitiveness and knowledgedevelopment. Strategic Management Journal 28 (10), 1035–1052.

Hult, G.T.M., Ketchen, D.J., Slater, S.F., 2004. Information processing, knowledgedevelopment, and strategic supply chain performance. Academy of ManagementJournal 47 (2), 241–253.

Ianchovichina, E., Martin, W., 2004. Impacts of China’s accession to the World TradeOrganization. The World Bank Economic Review 18 (1), 3–27.

Inkpen, A.C., 1998. Learning and knowledge acquisition through international strate-gic alliances. Academy of Management Executive 12 (4), 69–80.

Jaccard, J.J., Turrisi, R., Wan, C.K., 1990. Interaction Effects in Multiple Regression.Sage Publications, Newbury Park.

Jaworski, B.J., Kohli, A.K., 1993. Market orientation: antecedents and consequences.Journal of Marketing 57 (3), 53–70.

Jehn, K.A., 1997. A qualitative analysis of conflict types and dimensions in organiza-tional groups. Administrative Science Quarterly 42, 530–557.

Jiang, B., Frazier, G.V., Heiser, D., 2007. China-related POM research: a literaturereview and suggestions for future research. International Journal of Operations& Production Management 27 (7), 662–684.

Ketchen, D.J., Hult, G.T.M., 2007. Bridging organizational theory and supply chainmanagement: The case of best value supply chains. Journal of Operations Man-agement 25, 573–580.

Khanna, T., Gulati, R., Nohria, N., 1998. The dynamics of learning alliances: com-petition, cooperation, and relative scope. Strategic Management Journal 19 (3),193–210.

Kotzab, H., Teller, C., 2003. Value-adding partnerships and co-opetition models inthe grocery industry. International Journal of Physical Distribution & LogisticsManagement 33 (3), 268–281.

Kumar, K., Dissel, H.G.V., 1996. Sustainable collaboration: managing conflict andcooperation in interorganizational systems. MIS Quarterly 20 (3), 279–302.

Lado, A.A., Boyd, N.G., Hanlon, S.C., 1997. Competition, cooperation, and the searchfor economic rents: a syncretic model. Academy of Management Review 22 (1),110–141.

Lambert, D.M., Harrington, T.C., 1990. Measuring non-response bias in customermail surveys. Journal of Business Logistics 10, 44–59.

Langerak, F., 2001. Effects of market orientation on the behaviors of salespersons andpurchasers, channel relationships, and performance of manufacturers. Interna-tional Journal of Research in Marketing 18 (3), 221–234.

Lee, H.L., Padmanabhan, V., Whang, S., 1997. Information distortion in a supply chain:the bullwhip effect. Management Science 43 (4), 546–558.

Leung, K., Koch, P.T., Lu, L., 2002. A dualistic model of harmony and its implications forconflict management in Asia. Asia Pacific Journal of Management 19, 201–220.

Leung, T.K.P., Lai, K.H., Chan, R.Y.K., Wong, Y.H., 2005. The roles of xinyong and guanxiin Chinese relationship marketing. European Journal of Marketing 39, 528–559.

Li, Y., Liu, Y., Duan, Y., Li, M., 2008a. Entrepreneurial orientation, strategic flexibilitiesand indigenous firm innovation in transitional China. International Journal ofTechnology Management 41, 223–246.

Li, Y., Liu, Y., Zhao, Y., 2006. The role of market and entrepreneurship orientationand internal control in the new product development activities of Chinese firms.Industrial Marketing Management 35 (3), 336–347.

Li, Y., Liu, Y., Li, M., Wu, H., 2008b. Transformational offshore outsourcing: empir-ical evidence from alliances in China. Journal of Operations Management 26,257–274.

Liu, Y., Luo, Y., Liu, T., 2009. Governing buyer–supplier relationships through trans-actional and relational mechanisms: evidence from China. Journal of OperationsManagement 27 (4), 294–309.

Lumpkin, G.T., Dess, G.G., 1996. Clarifying the entrepreneurial orientation constructand linking it to performance. Academy of Management Review 21 (1), 135–172.

Luo, X., Slotegraaf, R.J., Pan, X., 2006. Cross-functional ‘co-opetition’: the simultane-ous role of cooperation and competition within firms. Journal of Marketing 70,67–80.

Luo, Y., 2005. Toward co-opetition within a multinational enterprise: a perspectivefrom foreign subsidiaries. Journal of World Business 40 (1), 71–90.

Luo, Y., 2007. A co-opetition perspective of global competition. Journal of WorldBusiness 42 (2), 129–144.

Lyles, M., Salk, J., 1996. Knowledge acquisition from foreign parents in internationaljoint ventures. Journal of International Business Studies 38, 3–18.

1 ns Ma

M

M

M

M

M

M

M

M

M

M

N

N

NO

P

P

P

P

R

R

R

S

S

S

S

S

S

S

S

S

42 Y. Li et al. / Journal of Operatio

ahoney, J.T., 1993. Strategic management and determinism: sustaining the con-versation. Journal of Management Studies 30 (1), 174–191.

allen, B., 1963. A theory of retailer–supplier conflict, control and cooperation.Journal of Retailing 39, 24–32.

assey, G.R., Dawes, P.L., 2007. The antecedents and consequences of functionaland dysfunctional conflict between marketing managers and sales managers.Industrial Marketing Management 36 (8), 1118–1129.

cEvily, B., Peronne, V., Zaheer, A., 2003. Trust as an organizing principle. Organi-zation Science 14, 91–103.

enon, A., Bharadwaj, S.G., Howell, R., 1996. The quality and effectiveness ofmarketing strategy: effects of functional and dysfunctional conflict in intraor-ganizational relationships. Journal of the Academy of Marketing Science 24 (4),299–313.

iller, D., 1983. The correlates of entrepreneurship in three types of firms. Manage-ment Science 29 (7), 770–791.

ione, A., 2009. When entrepreneurship requires coopetition: the need for stan-dards in the creation of a market. International Journal of Entrepreneurship andSmall Business 8 (1), 92–109.

ohr, J., Spekman, R., 1994. Characteristics of partnership success: partnershipattributes, communication behavior, and conflict resolution techniques. Strate-gic Management Journal 15, 135–152.

orrison, P.D., Roberts, J.H., von Hippel, E., 2000. Determinants of user innova-tion and innovation sharing in a local market. Management Science 46 (12),1513–1527.

uthusamy, S.K., White, M.A., 2005. Learning and knowledge transfer in strategicalliances: a social exchange view. Organization Studies 26 (3), 415–441.

onaka, I., Umemoto, K., Senoo, D., 1996. From information processing to knowledgecreation: a paradigm shift in business management. Technology in Society 18(2), 203–218.

ooteboom, B., Berger, H., Nooriderhaven, N.G., 1997. Effects of trust and governanceon relational risk. Academy of Management Journal 40 (2), 308–338.

unnally, J.C., 1978. Psychometric Theory. McGraw-Hill, New York.smonbekov, T., Bello, D.C., Gilliland, D.I., 2009. The impact of e-business infusion

on channel coordination, conflict and reseller performance. Industrial MarketingManagement 38 (7), 778–784.

arameswaran, R., Yaprak, A., 1987. A cross-national comparison of consumerresearch measures. Journal of International Business Studies 18, 35–49.

aulraj, A., Lado, A.A., Chen, I.J., 2008. Inter-organizational communication as a rela-tional competency: antecedents and performance outcomes in collaborativebuyer–supplier relationships. Journal of Operations Management 26 (1), 45–64.

odsakoff, P.M., Organ, D.W., 1986. Self-reports in organizational research: problemsand prospects. Journal of Management 12 (4), 531–544.

owell, W., 1987. Hybrid organizational arrangements: new form or transitionaldevelopment? California Management Review (Fall), 67–87.

awwas, M.Y.A., Vitell, S.J., Barnes, J.H., 1997. Management of conflict using indi-vidual power sources: a retailer’s perspective. Journal of Business Research 40,49–64.

enko, M., Carsrud, A.L., Brannback, M., 2009. The effect of a market orientation,entrepreneurial orientation, and technological capability on innovativeness: astudy of young biotechnology ventures in the United States and in Scandinavia.Journal of Small Business Management 47 (3), 331–369.

eve, T., Stern, L.W., 1979. Interorganizational relations in marketing channels.Academy of Management Review 4 (3), 405–416.

arkar, M.B., Echambadi, R.A.J., Harrison, J.S., 2001. Alliance entrepreneurship andfirm market performance. Strategic Management Journal 22 (6/7), 701–711.

euring, S., Muller, M., 2008. Core issues in sustainable supply chain management—ADelphi study. Business Strategy and the Environment 17 (8), 455–466.

hin, H., Collier, D.A., Wilson, D.D., 2000. Supply management orientation and sup-plier/buyer performance. Journal of Operations Management 18 (3), 317–333.

irmon, D.G., Hitt, M.A., Ireland, R.D., 2007. Managing firm resources in dynamicenvironments to create value: looking inside the black box. Academy of Man-agement Review 32 (1), 273–292.

kinner, S.J., Gassenheimer, J.B., Kelley, S.W., 1992. Cooperation in supplier–dealerrelations. Journal of Retailing 68 (2), 174–193.

olingen, R., Berghout, E., Kusters, R., Trienekens, J., 2000. From process improve-ments to people improvement: enabling learning in software development.Information and Software Technology 42 (12), 965–971.

ong, M., Droge, C., Hanvanich, S., Calantone, R., 2005. Marketing and technologyresource complementarity: an analysis of their interaction effect in two envi-

ronmental contexts. Strategic Management Journal 26, 259–276.

ong, M., Dyer, B., Thieme, R.J., 2006. Conflict management and innovation per-formance: an integrated contingency perspective. Journal of the Academy ofMarketing Science 34 (3), 341–356.

orenson, O., 2003. Interdependence and adaptability: organizational learning andthe long-term effect of integration. Management Science 49 (4), 446–463.

nagement 29 (2011) 128–142

Stern, L.W., Reve, T., 1980. Distribution channels as political economics: a frameworkfor comparative analysis. Journal of Marketing 44 (4), 52–64.

Strutton, D., Pelton, L., 1997. Scaling the great wall: The Yin and Yang of resolvingbusiness conflicts in China. Business Horizons 40 (5), 22–35.

Teece, D.J., 1986. Profiting from technological innovation: implications for inte-gration, collaboration, licensing and public policy. Research Policy 15 (6),285–305.

Thomas, K.W., 1976. Conflict and conflict management. In: Dunnette (Ed.), Hand-book of Industrial and Organizational Psychology. Rand-McNally, Chicago, IL,pp. 889–935.

Thomas, K.W., 1992. Conflict and conflict management: reflections and update. Jour-nal of Organizational Behavior 13, 265–274.

Tjosvold, D., Cho, Y., Park, H., Liu, C., Liu, W., Sasaki, S., 2001. Interdependence andmanaging conflict with sub-contractors in the construction industry in East Asia.Asia Pacific Journal of Management 18 (3), 295–313.

Tjosvold, D., Hui, C., Yu, Z., 2003. Conflict management and task reflexivity for teamin-role and extra-role performance in China. International Journal of ConflictManagement 12, 239–258.

Tjosvold, D., Su, F., 2007. Managing anger and annoyance in organizations in China:the role of constructive controversy. Group & Organization Management 32 (3),260–289.

Tse, D.K., Francis, J., Walls, J., 1994. Cultural differences in conducting intra andinter-cultural negotiations: a Sino-Canadian comparison. Journal of Interna-tional Business Studies 24, 537–555.

Upson, J.W., Ketchen, D.J., Ireland, R.D., 2007. Managing employee stress: a key to theeffectiveness of strategic supply chain management. Organizational Dynamics36 (1), 78–92.

Vickery, S.K., Jayaram, J., Droge, C., Calantone, R., 2003. The effects of an integrativesupply chain strategy on customer service and financial performance: an anal-ysis of direct versus indirect relationships. Journal of Operations Management21 (5), 523–539.

Walter, A., Auer, M., Ritter, T., 2006. The impact of network capabilities andentrepreneurial orientation on university spin-off performance. Journal of Busi-ness Venturing 21, 541–567.

Webb, K.L., Hogan, J.E., 2002. Hybrid channel conflict: causes and effects on channelperformance. Journal of Business & Industrial Marketing 17 (5), 338–356.

Webster, J., 1995. Networks of collaboration or conflict? Electronic data interchangeand power in the supply chain. Journal of Strategic Information Systems 4 (1),31–42.

Wiklund, J., 1999. The sustainability of the entrepreneurial orientation–performancerelationship. Entrepreneurship Theory and Practice 24, 37–48.

Wiklund, J., Shepherd, D., 2005. Entrepreneurial orientation and small business per-formance: a configurational approach. Journal of Business Venturing 20, 71–91.

Wong, Y.H., Tam, J.L., 2000. Mapping relationships in China: Guanxi dynamicapproach. Journal of Business and Industrial Marketing 15 (1), 57–70.

Xu, K., Jayaram, J., Xu, M., 2006. The effects of customer contact on conformancequality and productivity in Chinese service firms. International Journal of Qualityand Reliability Management 23 (4), 367–389.

Yin, E., Bao, Y., 2006. The acquisition of tacit knowledge in China: an empiricalanalysis of the ‘supplier-side individual level’ and ‘recipient-side’ factors. Man-agement International Review 46 (3), 1–22.

Yli-Renko, H., Autio, E., Sapienza, H.J., 2001. Social capital, knowledge acquisition,and knowledge exploitation in young technology-based firms. Strategic Man-agement Journal 22 (6/7), 587–613.

Young, L.C., Wilkinson, I.F., 1997. The space between: towards a typology of interfirmrelations. Journal of Business to Business Marketing 4 (2), 53–97.

Zahra, S.A., Covin, J.G., 1995. Contextual influences on the corporateentrepreneurship–performance relationship: a longitudinal analysis. Journal ofBusiness Venturing 10 (1), 43–58.

Zahra, S.A., Nielsen, A.P., Bogner, W.C., 1999. Corporate entrepreneurship, knowl-edge, and competence development. Entrepreneurship Theory and Practice 16(1), 7–25.

Zhao, X., Flynn, B.B., Roth, A.V., 2007. Decision sciences research in China: current sta-tus, opportunities, and propositions for research in supply chain management,logistics, and quality management. Decision Sciences 38 (1), 39–80.

Zhao, X., Huo, B., Flynn, B.B., Yeung, J.H.Y., 2008. The impact of power and relation-ship commitment on the integration between manufacturers and customers ina supply chain. Journal of Operations Management 26, 369–388.

Zhou, K.Z., Yim, C.K., Tse, D.K., 2005. The effects of strategic orientations on

technology- and market-based breakthrough innovations. Journal of Marketing69, 42–60.

Zhu, Q., Sarkis, J., 2004. Relationships between operational practices and perfor-mance among early adopters of green supply chain management practices inChinese manufacturing enterprises. Journal of Operations Management 22 (3),265–289.