A Global Analysis of Orientation, Coordination, and Flexibility in

Supply ChainsAyman Omar1, Beth Davis-Sramek2, Matthew B. Myers3, and John T. Mentzer3

1Kogod School of Business, American University2University of Louisville3University of Tennessee

Global supply chains are growing rapidly, and the ability to manage cross border logistics operations has become a necessity tomaintain a competitive advantage in a dynamic environment. This research addresses current gaps in the literature by investigating

the buyer–supplier integration dynamics in a global context with a focus on the antecedents and outcomes involved in the process.Empirical data from 320 U.S. based manufacturing companies that source from overseas was collected and used to test the framework.In addition to providing empirical evidence for the importance of orientation on collaboration, operational coordination, and integrationthis research explains how manufacturing companies can enhance the flexibility of their global suppliers and how that impact their logis-tics as well as overall firm performance. Managerial and research implications are provided as well as areas for future research.

Keywords: global supply chain management; global supplier integration; logistics performance

INTRODUCTION

Dynamic changes in manufacturing and supply strategiesand increased levels of global competition have broughtabout increased strategic attention to an integrated supplychain (Handfield et al. 1999; Ragatz et al. 2002; Kumar andKopitzke 2008; Manuj and Mentzer 2008; Chen et al. 2009a;Shoenherr 2009). Reflected by how much activities in onecompany are synchronized with the activities of its suppliersor customers (Stock et al. 1999), supply chain integrationhas become a strategic lever for performance improvement(Zailani and Rajagopal 2005), and firms are increasinglyemphasizing continuity and a ‘‘seamless’’ end-to-end pipeline(Frohlich and Westbrook 2001). Successful integrationallows firms to link their internal processes to external sup-pliers and customers, creating competitive advantagethrough leveraging interwoven activities and processes thatcannot be easily replicated (Mentzer et al. 2001).

This study contributes to the significant and growing bodyof global supply chain research examining the integration–performance link in several ways. Theoretically, this researchexamines global supplier integration (GSI) antecedents andoutcomes and builds a corresponding theoretical model usingstrategic management theory through the relational view ofcompetitive advantage. The central thesis of this theory isthat firms in a supply chain can develop relationships thatresult in interorganizational processes which allow them tosystematically identify valuable know-how and then integrateit across organizational boundaries (Dyer and Singh 1998).Unlike other theories of competitive advantage, the rela-tional view considers strategic relationships in the analysis

(Prior 2006), and consistent with this view, we examine aspecific relationship between a manufacturer and one of itskey global suppliers. Hence, strategic resources lie beyondthe boundaries of the firm (Das and Teng, 2000), and com-petitive advantage stems from competing as an integral partof a supply chain and no longer as individual firms (Greenand Inman 2005; Cagliano et al. 2006).

Because supply chain integration can encompass many linksin the supply chain, we narrow the scope of our research toGSI, and we examine this phenomenon through the lens of therelational view. Integration of suppliers with internal businessprocesses requires a set of skills that extend beyond mere orderplacement to managing supply bases and combining resourceswith key suppliers (Wagner 2003). Further, addressing GSI(where at least one member is located cross border) hasbecome particularly germane as the changing landscape andincreasing level of globalization creates new opportunities forfirms engaged in the global business environment (Mentzeret al. 2001; Kotabe and Murray, 2004). Since effective supplierintegration will be a key factor for firm survival (Ragatz et al.1997), further extension in a global context will be critical forfuture firm success and performance gains.

While there has been a tendency to focus on supplier inte-gration activities in new product development (e.g., Petersenet al. 2005a; Koufteros et al. 2007), there is a lack ofresearch in other contexts (Wagner 2003) and also in exam-ining supplier integration antecedents (Eltantawy et al.2009). We address this gap by examining how collaborationand the management of product and information flowsthrough operational coordination foster GSI. Further, there isa contention that integration involves a firm’s disposition tointegrate with suppliers, and this stems from cultural andattitudinal factors that result in fairly consistent behavior(Wagner 2003). Thus, to operationalize the activities andprocesses that facilitate structural integration, firms mustdevelop a managerial philosophy that becomes a key elementof strategy, enabling firms to see the implications and impor-

Corresponding author:Beth Davis-Sramek, Department of Marketing and Logistics,College of Business, University of Louisville, 152 College ofBusiness, Louisville, KY 40292, USA; E-mail: beth.davis@louisville.edu

Journal of Business Logistics, 2012, 33(2): 128–144� Council of Supply Chain Management Professionals

tance of an integrated approach to the supply chain (Mentzeret al. 2001; Hult et al. 2008). Therefore, we build on morerecent supply chain research and suggest that supply chainorientation (SCO) is a critical antecedent of GSI.

With recent calls to provide more empirical evidence ofthe relative and respective contributions of strategic supplierintegration (Swink et al. 2007; Eltantawy et al. 2009), ourextension of this growing body of research leads to the theo-retical model shown in Figure 1. We expect that GSI willpositively influence supplier flexibility, which in turn willimpact logistics efficiency and logistics effectiveness, and boththen impact overall firm performance. Finally, we hypothesizethat cultural distance (CD) between a buyer and an overseassupplier will negatively impact the relationship between SCOand both collaboration and operational coordination efforts.In sum, the theoretical contribution resides in illustrating acomprehensive picture of supplier integration in a globalcontext, which incorporates the impact to both the supplierthrough flexibility and to the manufacturer through increasedlogistics and financial performance.

THEORY BUILDING AND HYPOTHESES

In the following section, we first offer insights from the rela-tional view that will be the foundation for GSI and the cor-responding theoretical model. This discussion is followed bythe development of the theoretical constructs in the modeland the related hypotheses.

Relational view of competitive advantage

Research suggests that buyer–supplier relationships are shift-ing from transaction to relationship-oriented (Dwyer et al.1987; Davis-Sramek et al. 2007), with an emphasis onrealigning the supplier’s capabilities to the buyer’s needs(Sanchez-Rodriguez 2009). Just as internal processes, prac-tices, and people are assets, so are relational ones (Wagner2006). The relational view of the firm provides an alternative

route to competitive advantage compared to the industryand resource-based views (Dyer and Singh 1998). Advanta-ges of an individual firm are often linked to the network ofrelationships in which the firm is embedded, where criticalresources span firm boundaries and are entrenched ininterfirm routines and processes. Therefore, a singular focuson ‘‘the firm’’ limits the explanatory power of models thatattempt to explain firm performance, and firms can combineresources to realize an advantage through joint investments,knowledge exchange, combining valuable and scarceresources, and more effective governance mechanisms. Con-sequently, the focus is on the supplier–customer relationshipand the embedded routines when examining models predict-ing performance.

The relational view infers that performance is more signifi-cantly impacted when firms have the appropriate governancestructures in place (Cousins and Menguc 2006). Recent sup-ply chain research has examined supply chain integration asa vital governance mechanism (e.g., Frohlich and Westbrook2001; Narasimhan and Das 2001; Ragatz et al. 2002).Although ‘‘integration’’ is a broad term which describes avariety of structural linkages, firms can integrate differentelements of their operations, including those that are bothtangible (such as product flows and measurement), or intangi-ble (such as relationships and information) (Chen et al.2009b). Regardless of its specific application, the contentionis that firms which engage in integrative activities will out-perform less-integrated firms due to better alignment ofobjectives and business processes, operational coordination,and fit (Swink et al. 2007).

Global supplier integrationAs firms are being challenged to build superior supplychains, supplier integration represents one significant pro-gram in these efforts (Eltantawy et al. 2009). Strategic sup-plier relationships represent a potent source of competitiveadvantage stemming from the interorganizational collectivelearning and a long-term focus on upgrading processes androutines in the manufacturer–supplier interface (Wagner

Collabora on

Opera onalCoordina on

Supply ChainOrienta on

GlobalSupplier

Integra on

SupplierFlexibility

Logis csEfficiency

Logis csEffec veness

OverallPerformance

h1

h2

h3

h4a

h5a

h6

h7

h8

h10

h9

Rela onshipOrienta on

Supplier Rela onshipIntegra on andPerformance

FirmPerformance

CulturalDistance

h11a

h11b

h11c

h5b

h4b

Figure 1: Theoretical framework.

Orientation, Coordination, and Flexibility in Global Supply Chains 129

2006). We focus specifically on GSI, which is defined in thiscontext as the level in which activities between a manufac-turer and a global supplier are structured and synchronized(Cagliano et al. 2006; Koufteros et al. 2007; Swink et al.2007). GSI allows manufacturers to meet production require-ments through developing and effectively exploiting bothsupplier and plant capabilities and cost structures (Swinket al. 2007). Therefore, an understanding of the drivers ofGSI is essential in order to enhance the advantages affordedto companies that initiate GSI activities.

Supplier flexibilitySupplier integration outcomes typically consist of uniquelinks with suppliers that facilitate the flow and quality ofmaterials into and out of buying firms (Eltantawy et al.2009). The relational view suggests that GSI should impactperformance for both the manufacturer and the supplierthrough integration behaviors and mechanisms (Cousins andMenguc 2006). While integration is studied in the context ofperformance outcomes for the manufacturing firm, researchis limited in examining the supplier outcomes of integration.

We extend this stream of research by focusing on supplierflexibility, defined as the manufacturer’s perception of thesupplier’s ability to respond to changes in the environment,including changes in supply and demand or changing risklevels in the home country (Christopher, 2000). While flexi-bility has been most commonly associated with the manufac-turing flexibility literature, (e.g., Upton 1995), more recentliterature has extended this view to the broader supply chain(Krajewski et al. 2005) to include more explicit interfirm ele-ments (Kumar et al. 2006). This research stream remains lim-ited, however, and there has been a call to include studiesthat incorporate the flexibility created by both upstream anddownstream supply chain partners (Stevenson and Spring2009).

Antecedents to GSI and supplier flexibility

Supply chain orientationRecent evidence found that obstacles hampering supplierrelationships include behavioral elements such as lack oftrust, disparate goals, and incongruent communication struc-tures (Forslund and Jonsson 2009). Another study foundthat some firms are more ‘‘inclined’’ to integrate suppliersthan others, citing a strong relationship between the degreeof supplier integration and cultural or attitudinal factors(Wagner 2003). The relational view indicates that relation-ships which create competitive advantage require firms toview exchange partners as collaborators rather than adver-saries (Dyer and Singh 1998). For firms that encourage GSI,employees must do different things, make different decisions,and perform in different ways (Kim, 2009). They must beable communicate efficiently with their suppliers, and often,this involves a significant attitudinal shift for firms (Cousinsand Menguc 2006).

Given this disposition needed for GSI, SCO has beendefined in the literature as the mindset that cooperation,mutual dependence, trust, and shared goals between supplychain partners positively impact performance (Mentzer et al.

2001). Therefore, SCO is a philosophy adopted by firmsto facilitate GSI, while supply chain management is theimplementation of the philosophy. Consistent with previousresearch (Min et al. 2007), we model SCO as a multi-dimensional, second order factor that incorporates thebehavioral elements necessary for creating the mindset facili-tating the orientation for integration. Trust is the extent ofconfidence the manufacturer has in the supplier’s integrityand the perception that the supplier will fulfill its obligations(Moorman et al. 1993). Commitment is the manufacturer’senduring desire to maintain a valued relationship with thesupplier (Moorman et al. 1993). Cooperative norms are themanufacturer’s perceptions of the joint efforts betweenthe firm and its supply chain members to achieve its goals(Siguaw et al. 1998). Organizational compatibility refers tothe degree that the manufacturer and global supplier havesimilar cultures and management styles (Bucklin and Seng-upta 1993). Finally, top management support is the amountof encouragement and motivation provided by top manage-ment to work with the supplier and maintain a strong rela-tionship with them (Jaworski and Kohli 1993). Thecollection of these relational variables reflect an organiza-tional culture that is an antecedent to successful execution ofnetworking with supply chain partners.

Operational coordination and collaborationFor this research, we view operational coordination as themanagement of systems, processes and product flow, and thealignment of decisions between the manufacturer and a glo-bal supplier (Sahin and Robinson 2002). It allows for activi-ties which facilitate better alignment with global supplychain objectives (Fugate et al. 2006) and represents the moreoperational and tangible elements concerned with better syn-chronization of short-term flows, including transactions,materials movements, and order processes (Swink et al.2007). Additionally, we focus on collaboration, which hasoften been used interchangeably with coordination (Zachariaet al. 2009). We distinguish the two, however, by proposingthat operational coordination reflects more tangible elementswhile collaboration is the informal behavior that occursbetween the manufacturer and global supplier based onresource and information sharing. Behaviors that encourageinformation, knowledge, and resource exchange must bepresent in supply chain relationships for firms to achievecommon goals or objectives (Ellinger et al. 2000).

As Figure 1 illustrates, SCO is a necessary prerequisite ofoperational coordination, collaboration, and GSI. Establish-ing the organizational relationships among partners toattain system and operational coordination and collabora-tion is a challenging task, but research suggests that volun-tary (vs. contractual or adversarial) information exchangeand collaboration are more effective in informal and‘‘close’’ manufacturer–supplier exchanges (Frazier et al.1988). Governance structures that employ informal safe-guards such as trust and commitment are more likely todecrease conflict, increase cooperation, and encourage long-term relationships (Morgan and Hunt 1994). The relationalview also proposes that advantage is realized if firms havecompatible cultures which facilitate coordinated action and

130 A. Omar et al.

collaborative decision-making processes (Dyer and Singh1998). Therefore, we contend that the extent of GSI shouldlikewise be impacted by the overall philosophy (mindset) ofthe manufacturer.

H1: Supply chain orientation is positively related to col-laboration.

H2: Supply chain orientation is positively related tooperational coordination.

H3: Supply chain orientation is positively related to glo-bal supplier integration.

Firms that pursue integration with suppliers create struc-tures and operational linkages, and develop behaviors thatenhance GSI (Metcalf et al. 1992; Wagner 2003). Two key ele-ments that need to be present between companies to have anintegrated relationship are collaboration and operationalcoordination (Ellinger et al. 2002; Fugate et al. 2006). There-fore, antecedents that facilitate integration include both objec-tive elements akin to operational coordination and behavioralelements suggestive of collaboration (Petersen et al. 2005b).In line with the relational view, competitive advantage is cre-ated when firms develop superior overlapping knowledgebases and interaction routines (Dyer and Singh 1998). Alsoconsistent with the literature, integration requires firms totake deliberate steps to coordinate and collaborate with selectglobal suppliers in order to jointly achieve objectives (Chenet al., 2009b). Further, by strengthening relationships withglobal supply chain members, firms can develop a unique setof capabilities to enhance flexibility, which helps to reduceconcept-to-customer cycle time, costs, and quality problems(Ragatz et al. 2002). Thus, we expect that collaboration andoperational coordination between a firm and its supplier willdirectly impact supplier flexibility (Tracey 2004).

H4: Collaboration is positively related to (a) global sup-plier integration, and (b) supplier flexibility.

H5: Operational coordination is positively related to (a)global supplier integration, and (b) supplier flexibility.

Outcomes of GSI

There have been previous calls for further empirical researchon the link between integration and performance (Stanket al. 2001; Wisner 2003; Rodrigues et al. 2004). Given thatthe relational view offers support for competitive advantagespecific to the buyer–seller relationship, integration with akey global supplier should impact performance. As Figure 1illustrates, this research models performance outcomes con-sistent with previous research which maintains that theimpact of integration on firm performance is mediated by‘‘intermediate’’ performance outcomes (e.g., Vickery et al.

2003; Droge et al. 2004; Cousins and Menguc 2006). Theproceeding hypotheses reflect the expected outcomes of GSI,including the relationships among GSI, supplier flexibility,logistics efficiency, logistics effectiveness, and overall firmperformance.

In a constantly changing environment, flexibility providesfirms the capacity to adapt, and integration is a necessaryprerequisite given the nature of interfirm dependence(Tracey 2004). Several studies have supported the notionthat higher levels of integration between supply chain part-ners are crucial for improved responsiveness and higherflexibility (e.g., Daugherty et al. 2006; Paulraj and Chen2007). When the manufacturer and supplier are engaging incollaborative behaviors and managing product and informa-tion flow the result is a stronger structural integrationbetween both firms. This increased level of integrationshould allow suppliers to more quickly and efficientlyrespond to changes when they arise.

Early supplier involvement, partner development, opportu-nity to leverage partner competency, and relationship com-mitment can lead to greater flexibility in supply chains.Effective processes achieved through GSI may enhance orga-nizational responsiveness (Damanpour and Gopalakrishnan,2001; Khazanchi et al. 2007), providing firms with organiza-tional practices and expertise that could be used for develop-ing alternative solutions and improving the overalloperational and market flexibility (Azadegan and Dooley2010). Therefore, we expect that greater flexibility will beachieved when there is more interaction and learning amongsupplier chain members which allow them to adapt quicklyand swiftly to unforeseen changes in the environment.

H6: Global supplier integration is positively related tosupplier flexibility.

Logistics and firm performanceGiven the contention that GSI increases supplier flexibility,research which subsequently examines the effect on the man-ufacturer’s performance remains negligible (Avittathur andSwamidass 2007). This research models the outcomes associ-ated with performance related to logistics processes, specifi-cally, logistics efficiency (the function of resources utilized)and logistics effectiveness (the extent to which goals areachieved). When a global supplier can respond to unexpectedchanges in customer demand or the environment, the manu-facturer can improve efficiency by reducing redundancies,conflicts, and confusion, all of which can decrease the associ-ated logistics costs. Supplier flexibility also allows for a moreunified response to shorten the time required to match sup-ply and demand, lowering investments in overall logisticscosts (Fugate et al. 2009).

H7: Supplier flexibility is positively related to logisticsefficiency.

Supplier flexibility enables the manufacturer to meet thesegoals through aligning the ‘‘promise to deliver’’ made bythe manufacturer with the actual delivery. Effectiveness will

Orientation, Coordination, and Flexibility in Global Supply Chains 131

also improve when greater supplier flexibility results in afaster response which should increase the likelihood ofmeeting deadlines for pre-defined goals. Thus, the custom-ers’ perceived quality of delivered product and service isenhanced.

H8: Supplier flexibility is positively related to logisticseffectiveness.

Finally, as supported by previous research (e.g., Stanket al. 1999; Ellinger et al. 2000; Fugate et al. 2009), we exam-ine the logistics performance fi firm performance relation-ship. Higher levels of logistics efficiency results from anelimination of waste, lower expenses, and reductions ininventory and cash (Mentzer and Konrad 1991), all of whichincrease return on assets and earnings. Likewise, logisticseffectiveness can impact customer satisfaction and repeatpurchasing, increasing top-line revenue.

H9: Logistics efficiency is positively related to firm per-formance.

H10: Logistics effectiveness is positively related to firmperformance.

The moderating effects of national CDCulture is the interactive aggregate of common characteris-tics that influence a group’s response to its environment(Cheung et al. 2010). Culture is a multilevel concept wherevarious levels of cultural phenomena are nested within eachother from the macro level of global culture, throughnational cultures, organizational cultures, group cultures,and individual’s cultural values (Leung et al. 2005). Of thesetypes, national culture is most often examined in interna-tional marketing research and has been defined as patternsof thinking, feeling, and acting rooted in common beliefsand conventions of society (Nakata and Sivakumar 1996)Traditionally, cross-national research rests on the premise ofculturally founded norm expectations being embedded inbilaterally established relational strategies (Griffith andMyers 2005; Cannon et al. 2010).

Intercultural exchange scenarios are determined jointly bydyad partners, and are embedded with national cultural ele-ments of each party in the exchange. Previous research onintercultural encounters in the functioning of multinationalbusiness organizations has suggested that CD between thecountries representing exchange partners will influence man-agerial decision making in a global business environment(Kogut and Singh 1988). These differences may cause dis-parity in the levels of commitment, trust, dependence, andshared goals of exchange partners (Cheung et al. 2010).Relational norm governance mechanisms, including theexchange of knowledge and information between partners(Zhang et al. 2003), are specific to each exchange partnerand differ significantly depending on culturally establishedexpectations. For example, collectivism can moderate therelationship between dependence (a key SCO component)

and relational governance mechanisms such as cooperationand coordination (see Roath et al. 2002). Cross-border buy-ers and suppliers that have similar national cultures willhave less disparity in the way they view the value of shar-ing information (Cheung et al. 2010) and have a strongerpropensity to coordinate operations collaborate on opera-tionally related decisions, and establish more integratedsupply chain structures.

From this research, we hypothesize that the effects of SCOon collaboration and operational coordination mechanismsare negatively influenced by CD between exchange partners.We define CD as the difference in national culture betweenthe home country of the manufacturer and the home countryof the supplier (Hofstede 1980; Hutzschenreuter and Voll2008). These cultural dimensions moderate how supply chainpartners perceive buyer–seller exchanges, and the greater theCD between partners, the less likely the SCO of the firm willhave positive benefits on collaboration, operational coordi-nation, and integration. Thus:

H11: Cultural distance has a negative influence on therelationships between supply chain orientation and(a) collaboration, (b) operational coordination,and (c) global supplier integration.

RESEARCH METHOD

The sampling procedure

In order to test the proposed theoretical model, we focusedon manufacturing firms based in the United States thatsource from global suppliers. Consistent with the contentionsof the relational view, we drew out perceptions of the rela-tionship between the manufacturer and a key global supplier.The unit of analysis was the manufacturer’s perception ofthe relationship with a key global supplier. Supply chainexperts and purchasing and logistics managers ensured con-tent validity and assisted in a pretest.

The pretest was conducted in order to validate the mea-sures in this research and to identify potential problemsrelated to face validity. The process also provided face valid-ity of the measures. The five step process recommended byDillman (2000) was used for the implementation of the pre-test survey. The pretest was administered through a web-based survey, following Dillman (2000) using a list of manu-facturers across multiple industries provided by InfoUSA.From 425 contacts that qualified over the phone, 103resulted in completed online surveys, yielding a response rateof 24%. Respondents answered 77 substantive questionsrelated to the theoretical framework and 17 questions cap-turing control variables and ⁄or demographic-type questions.

The small sample size precluded use of confirmatory factoranalysis (CFA), thus principal component factor analysesassisted the evaluation of scale unidimensionality and Cron-bach’s coefficient alpha assessed scale reliability (Selnes andSallis 2003). Scales containing more than three items wereexamined for potential improvement by assessing item–total

132 A. Omar et al.

correlation, communalities, Cronbach’s alpha if-item-deleted,and the inter item correlation matrix. Preliminary evidencefor discriminant validity also relied on principal componentsanalysis and correlation matrices. In summary, the pretestoffered provisional validation for both the newly developedmeasures and literature-based scales.

The final population frame was drawn from a list of manu-facturers across multiple industries supplied by InfoUSA. Theinitial list had 5,000 contacts. Pre qualification phone callswere made, and after identifying contacts that did not haveadequate supply chain knowledge, did not do business withglobal suppliers, or could not be reached, the sampling framecontained 1,452 entries. From this, 855 respondents agreed totake the online survey, each of whom were mid- and top-levellogistics, purchasing, or supply chain managers, and had first-hand knowledge of their supplier relationships. After follow-up phone calls to ensure participation, the final sampleyielded 320 responses (320 ⁄ 855 = 37% response rate).

The average relationship age between manufacturers sur-veyed and their corresponding suppliers was 6 years. Less than1% of the respondents reported annual sales of under $1 mil-lion, while 11% had sales of over $500 million. Sixty percentof respondents held job levels of director or higher, with theremaining reporting middle-level manager positions (e.g., pur-chasing manager or materials manager). Firms came from thefollowing industries: apparel ⁄ textiles, appliances, automotive,chemicals ⁄plastics, consumer packaged goods, electronics,industrial products, medical ⁄pharmaceutical, and aerospace.Table 1 provides detail based on the primary three-digit NA-ICS distribution. The respondents discussed a diverse range ofglobal suppliers that spanned across 33 countries. Table 2 liststhe home country of the global suppliers.

Capturing nonrespondent’s verbal answers to five itemsand testing for differences against survey data responsesallowed for potential response bias evaluation (Mentzer andFlint 1997). Specifically, 110 nonrespondents who had previ-ously indicated they were qualified—but not interested orcapable to take the survey due to time constraints—werecontacted by phone and asked to respond to five questions

(four items from the collaboration scale and their job title).No significant differences (p £ .05) were found between itemsand verbal responses.

Measurement scalesSCO was modeled as a second order reflective construct withfive dimensions, which is consistent with other research mea-suring SCO (e.g., Min et al. 2007). The items used to mea-sure SCO were adapted from the existing literature with eachscale having seven points labeled strongly disagree (=1) tostrongly agree (=7). Items for trust were adapted from Do-ney and Cannon (1997); commitment and cooperative normsitems were adapted from (Siguaw et al. 1998); organizationalcompatibility items were adapted from Min et al. (2007); andtop management support items were adapted from Jaworskiand Kohli (1993). Since SCO was a second order construct,a two step approach was taken to construct a compositescale to be used in the overall CFA and structural models.Table 3 outlines the SCO dimensions (trust, commitment,

Table 1: Sample industry distribution

Three-digit NAICS n %

311 Food 23 7313 Textile mills 26 8315 Apparel 24 8321 Wood products 31 10322 Paper 26 8324 Petroleum and coal products 25 8325 Chemicals 28 9326 Plastics and rubber products 25 8332 Fabricated metal products 24 8333 Machinery 27 8334 Computers and electronics 38 12336 Transportation equipment 23 7

Total 320

Note: NAICS, North American Industry Classification System.

Table 2: Home country of global suppliers

Country of supplier n %

Australia 1 0.3Austria 1 0.3Bolivia 1 0.3Brazil 6 1.9Canada 41 12.8China 102 31.9Denmark 2 0.6Ecuador 1 0.3Finland 2 0.6France 7 2.2Germany 25 7.8Greece 1 0.3India 11 3.4Indonesia 1 0.3Ireland 1 0.3Israel 2 0.6Italy 10 3.1Japan 23 7.2Kazakhstan 1 0.3Malaysia 3 0.9Mexico 22 6.9Netherlands 2 0.6Poland 1 0.3Portugal 1 0.3Russia 1 0.3S. Korea 6 1.9Spain 4 1.3Sweden 4 1.3Switzerland 5 1.6Taiwan 15 4.7Thailand 3 0.9UK 12 3.8Venezuela 2 0.6Total 320 100

Orientation, Coordination, and Flexibility in Global Supply Chains 133

cooperative norms, organizational compatibility, and topmanagement support) and offers the item-to-item correla-tions. All items demonstrated good discriminant and conver-gent validity, reliability, and a good fit statistics of the CFAmodel. Second, a composite scale for SCO was establishedwith five items representing the mean of each of the fivedimensions.

Collaboration was measured by asking respondents toindicate the level of resource, information, and knowledgesharing that takes place between their firm and their globalsupplier with items adapted from Stank et al. (2001) andMin et al. (2007). Respondents reflected on operational coor-dination by indicating the degree of mechanisms used toalign product flow and movement between their firm andtheir supplier (Sahin and Robinson 2002; Romano, 2003)with items adapted from Jap (2001). GSI was measuredthrough items adapted from Narasimhan and Das (2001)and Swink et al. (2007) to assess the overall level of struc-

tural integration with a key global supplier. Flexibility wasmeasured by assessing how well the supplier could adaptunder changing conditions of supply, demand, and the exter-nal environment (Swafford et al. 2008).

Performance constructs were anchored by seven pointscales which compared the manufacturers’ performance withthat of their competitors. Adapted from Fugate et al. (2009),logistics efficiency was assessed by asking how well costobjectives were met, and logistics effectiveness was measuredby asking the extent to which logistics objectives had beenachieved relative to competition. Firm performance was mea-sured by perceptions of firm performance relative to compe-tition along the dimensions of profitability and growth (Minet al. 2007). All survey items are shown in Table 4.

CD was measured by incorporating Hofstede’s (1980, 2001)framework which identifies five dimensions of cultural varia-tion among nations. They include uncertainty avoidance, indi-vidualism versus collectivism, power distance, masculinity

Table 3: Supply chain orientation (SCO) dimensions and items

Scale Reliability Items Mean SD

Item-to-total

correlation

Trust 93 (T1) This supplier is trustworthy 4.28 1.60 .84(T2) We believe that this supplier keeps our bestinterest in mind

4.87 1.65 .89

(T3) This supplier is genuinely concerned that ourbusiness succeeds

4.24 1.68 .88

Commit. 91 (COM1) We expect our relationship to continue withthis supplier for a long time

5.31 1.45 .81

(COM2) We will do what it takes to preserve ourrelationship with this supplier

4.96 1.48 .84

(COM3) The continuity of our relationship with thissupplier is very important to us.

5.23 1.47 .84

Norms 93 (NRM1) We believe our supply chain members mustwork together to be successful

5.54 1.93 .90

(NRM2) We view our supply chain as a value addedpiece of our business

5.52 1.94 .92

(NRM3) We believe we can improve our performanceby adapting to any necessary changes with oursupplier

4.74 1.90 .82

Comp. 91 (CMP1) The culture of our firm is similar to that ofthis supplier.

3.68 1.68 .82

(CMP2) Our executives have a management stylesimilar to this supplier

3.50 1.62 .85

(CMP3) Our firm has a compatible corporate cultureto that of our supplier.

3.67 1.64 .83

TMS 88 (TMS1) Top managers repeatedly encourageemployees to maintain our relationship with thissupplier

4.54 1.52 .79

(TMS2) Top managers repeatedly tell employees thatsharing valuable strategic ⁄ tactical information withour supplier is important to improve our performance

3.97 1.67 .84

(TMS3) Top management supports a stronger workingrelationship with our supplier

4.72 1.48 .78

SCO fit statistics: v2 = 138.37, df = 80, v2 ⁄ df = 1.729, comparative fit index (CFI) = .98, and root mean square error of approximation

(RMSEA) = .048.

134 A. Omar et al.

versus femininity, and long term versus short term orientation.This secondary data set was developed to assess cultural char-acteristics of individual countries. The dimensions were devel-oped on the basis of over 100,000 survey respondents in 66countries and are most representative of middle class individu-

als in multinational corporations from which the sample wasdrawn. In calculating CD between two nations, represented bythe cross-border dyadic exchange relationships of our respon-dents who are native managers to the country where theywork, we followed Kogut and Singh’s (1988) method and use

Table 4: Main survey items

Scale Reliability Items Mean SD

Collaboration 93 (COL1) We share information with our supplier on operationaldecisions

3.49 1.81

(COL2) We share knowledge and specific know–how with oursupplier on operational decisions

3.63 1.89

(COL3) We work closely with our supplier on issues related tooperational decisions

3.54 1.86

Operationalcoordination

90 (COR1) We coordinate operations with our supplier 3.73 1.79(COR2) Our firm and this supplier have systems or processes inplace to facilitate the movement and flow of products

4.22 1.76

(COR3) We use one or more mechanisms to coordinateoperations with our supplier

4.23 1.76

Integration 79 (OPI1) We have a high level of process integration with thissupplier

4.03 1.67

(OPI2) Our operations are integrated with this supplier 4.68 1.59(OPI3) We emphasize early supplier involvement in newproduct development with this supplier

4.57 1.65

Flexibility 89 (FLEX1) This supplier can respond quickly to unexpectedchanges in demand

3.72 1.45

(FLEX2) This supplier can respond quickly to unexpectedchanges in supply

3.78 1.31

(FLEX3) This supplier can respond quickly to unexpectedpolitical changes in the supplier’s home country

3.91 1.38

(FLEX4) This supplier can respond quickly to unexpectedeconomic changes in the supplier’s home country

4.14 1.76

(FLEX5) This supplier can respond quickly to unexpectedactions by our competitors

4.27 1.82

Logistics efficiency 88 Relative to competition in the previous fiscal year, ourperformance was (much worse or much better)

(OE1) Warehousing costs 4.56 1.89(OE2) Inventory costs 4.54 1.30(OE3) Order processing costs 4.66 1.84(OE4) Overall logistics costs 4.60 1.72

Logisticseffectiveness

81 Relative to competition in the previous fiscal year, ourperformance was (much worse or much better)

(OF1) Number of back orders ⁄ stock-outs 4.55 1.43(OF2) Time between order receipt and order delivery 4.98 1.35(OF3) Shipping errors 4.63 1.41(OF4) Damage free goods 4.81 1.44

Firm performance 92 (FP1) Our business unit’s return on assets relative to ourcompetitors

4.74 1.21

(FP2) Our business unit’s return on investment relative to ourcompetitors

4.66 1.26

(FP3) Our business unit’s return on sales relative to ourcompetitors

4.72 1.87

(FP4) Our business unit’s sales growth relative to ourcompetitors

4.76 1.65

(FP5) Our business unit’s market share growth relative to ourcompetitors

4.70 1.39

Orientation, Coordination, and Flexibility in Global Supply Chains 135

Hofstede’s indices to form a composite index for CD basedupon the deviation along each of the cultural dimensionsbetween the two nations.

Measurement model validationEvaluation of measures began by grouping items into a pri-ori conceptualized construct scales and examining theircapacity to demonstrate unidimensionality, convergent anddiscriminant validity, and reliability. To assess overall mea-surement fit within CFA, the measurement model was run inAMOS 7. The CFA fit statistics were good (v2 = 747.4,df = 433, v2 ⁄df = 1.726, CFI = .95, and RMSEA = .048)(Garver and Mentzer 1999).

All factor loadings were statistically significant, indicatinggood convergent validity. Discriminant validity was exam-ined by the nested models approach, where a series of nestedmodels were specified that constrained the covariancebetween clusters of constructs to one (Anderson and Gerbing1982). Constrained models were compared to baseline mod-els that allowed parameters to correlate freely. Analysesrevealed all differences between constrained and uncon-strained models were significant (p £ .05), indicating that dis-tinct theoretical constructs posed a better fit. The averagevariance extracted (AVE) was computed for each constructand compared to the shared variance between all possiblepairs of constructs (Fornell and Larcker 1981). All compari-sons met the stated criteria where AVE was greater thanshared variance (see Table 5). Finally, all constructs hadgood reliability and fell within the acceptable range.

Logistics and firm performance measures were self-reported in this study. Several previous studies demonstratethat self-reported performance assessment is consistent withexternal secondary data and objective internal performance(Tan et al. 1999; Kannan and Tan 2006; Fugate et al. 2009).A total of 65 respondents voluntarily provided their firmnames, which were also available in the Compustat database.Three objective indicators (return on investment, return onassets, return on sales, and sales growth) obtained via Com-pustat for the 65 companies were compared with the Likert-scale measures. This resulted in a positive, significant correla-tion of .72 for return on investment, .69 for return on assets,and .66 for return on sales, each significant at p < .01.

RESULTS

The hypotheses were tested using AMOS 7.0 and the stan-dardized regression weights of each relationship are shownin Table 6. The overall fit of the structural model was goodand all of the fit statistics were within the acceptable range(v2 = 1,004.31, df = 449, v2 ⁄df = 2.23, CFI = 0.92, andRMSEA = .062).

As depicted in H1 through H3, higher levels of SCO leadto higher levels of collaboration (standardized regressionweight = .249, p < .001), operational coordination (stan-dardized regression weight = .323, p < .001), and GSI(standardized regression weight = .394, p < .001) with akey global supplier.

H4a and H5a predicted that higher levels of collaborationand operational coordination would lead to higher levelsGSI. Both of those hypotheses were supported (standardizedregression weights = .345, p < .001 and .485, p < .001,respectively). H4b and H5b predicted that higher levels of col-laboration and operational coordination would lead tohigher levels of supplier flexibility. Neither of these hypothe-ses were supported (standardized regression weights = .12,p = .13 and .13, p = .18, respectively). Higher levels of GSIlead to higher levels of supplier flexibility as predicted in H6

(standardized regression weight = .554, p < .001). H7 pre-dicted that higher levels of supplier flexibility will improvelogistics efficiency. This was supported (standardized regres-sion weight = .239, p < .001). This was also the case for H8

where higher levels of supplier flexibility was hypothesized asa predictor for improved logistics effectiveness (standardizedregression weight = .269, p < .001).

Finally, H9 and H10 predicted a positive relationshipbetween logistics efficiency and firm performance as well asthe relationship between logistics effectiveness and firm per-formance, respectively. Both hypotheses were supported (H9,standardized regression weight = .39, p < .001 and H10,standardized regression weight = .318, p < .001) indicatingthat improvements in logistics efficiency and effectiveness dolead to an overall improvement in firm performance.

The Sobel test (Sobel 1982) was used to directly examine thesignificance of mediation effects. This test is superior to testfor mediation effects in terms of power and intuitive appeal

Table 5: Average variance extracted (AVE)

SCO Collab. Op. coord. GSI Flex. Efficiency Effect. Perform.

SCO .639

Collab. .226 .8318

Op. Coord. .276 .4747 .7632

GSI .297 .4543 .5730 .6703

Flex. .089 .0437 .0655 .1183 .5870

Efficiency .076 .0339 .0620 .0818 .1520 .6517

Effectiveness .094 .0210 .0437 .0718 .2655 .2632 .6824

Perform .035 .0029 .0146 .0313 .0286 .2510 .2323 .6848

Notes: Diagonal (bolded values) = AVE; Lower matrix = R2.

GSI, global supplier integration; SCO, supply chain orientation.

136 A. Omar et al.

(Mackinnon et al. 2002; Carey et al. 2011). We found strongsupport for the role of GSI in fully mediating collaboration tosupplier flexibility (t = 4.64, p < .01), and operational coor-dination to supplier flexibility (t = 4.82, p < .01). We alsofound strong support for the role of supplier flexibility in fullymediating GSI to logistics efficiency (t = 2.59, p < .01) andGSI to logistics effectiveness (t = 2.62, p < .01).

In order to test the moderating effect of CD, we conductedmultiple-group analyses to examine whether the effects ofSCO on collaboration and operational coordination aremoderated by CD (Figure 1). The scores for CD for eachsupplier home country were calculated using the method sug-gested by Kogut and Singh (1988).1 The scores of each cul-tural dimension as well as the values for the CD between thehome country of the manufacturer (USA in this research)and the host country (supplier home country) are shown inAppendix. The data were then dichotomized by groupingCD scores into two categories—low CD and high CD.2

Finally, the parameters of interest (i.e., the paths from SCOto collaboration, SCO to operational coordination, and SCOto GSI) were labeled in order to constrain the estimates oftheir values and the fit statistics of the two models were com-

pared (constrained vs. unconstrained). The first model wasthe moderated model (paths were free to vary). In the secondmodel, the no-moderation model, each path was constrainedonce (Path 1 High = Path 1 Low, Path 2 High = Path 2Low, etc.). Therefore, the no-moderation model constrainedthe path weights to be the same regardless of the level ofCD, while the moderation model allowed for differences inCD to change the path weights. The two models were thencompared to check for differences in fit. The nested modelcomparison showed no significant difference between themoderated model and the no-moderation model. In all threecases (H11a, H11b, and H11c), the moderating effects of CDwere not statistically significant (p > .05). Therefore, weconcluded that the effects of SCO on collaboration, opera-tional coordination, and GSI are not moderated by CD.

DISCUSSION

Global competition compels firms around the world to re-think their approach to a market increasingly characterizedby a network of competing global supply chains. The trendtoward globalization has intensified business competitionand resulted in shrinking profit margins in many industries,leading the nature of competition to evolve to pairs and net-works of allied firms (Eltantawy et al. 2009). Therefore, thesupply chain management concept and its implementationare predicated on integration across the supply chain (Pagell2004; Green and Inman 2005).

Theoretical implications

In support of calls to address gaps in knowledge about globalsupply chain management, the purpose of this study was totest a theory of supplier integration in a global business

Table 6: Summary of results

Hypothesis and description

Standardized

regression weight Significance (p<) Conclusion

H1: SCO fi Collaboration .251 .001 SupportedH2: SCO fi Operational coordination .326 .001 SupportedH3: SCO fi GSI .378 .001 SupportedH4a: Collaboration fi GSI .334 .001 SupportedH4b: Collaboration fi Supplier flexibility .12 .13 Not supportedH5a: Operational coordination fi GSI .478 .001 SupportedH5b: Operational coordination fi Supplier flexibility .13 .18 Not supportedH6: GSI fi Supplier flexibility .366 .001 SupportedH7: Supplier flexibility fi Logistics efficiency .238 .001 SupportedH8: Supplier flexibility fi Logistics effectiveness .267 .001 SupportedH9: Logistics efficiency fi Firm performance .390 .001 SupportedH10: Logistics effectiveness fi Firm performance .318 .001 SupportedH11a: CD moderates SCO fi Collaboration N ⁄A .131 Not supportedH11b: CD moderates SCO fi Operational coordination N ⁄A .180 Not supportedH11c: CD moderates SCO fi GSI N ⁄A .832 Not supported

CD, cultural distance; GSI, global supplier integration; SCO, supply chain orientation.

1 We followed Kogut and Singh (1988) and used Hofstede’sindices to form a composite index for CD based upon thedeviation along each of cultural dimensions between the twocountries.

CDbs ¼P4i¼1

Iib � Iisð Þ2=Vi

n o=4 where Ii stands for the index

for the ith cultural dimension, and b indicates the buyercountry, Vi is the variance of the index of the ith dimension,s indicates the supplier country, and CDbs is the cultural dis-tance between the buyer country and the supplier country.2 We ran a similar test using groups dichotomized by a med-ian split, with no significant differences in results.

Orientation, Coordination, and Flexibility in Global Supply Chains 137

context. Extending the supply chain integration literature toencompass the relational view of the firm (Dyer and Singh1998), we suggest that a manufacturer and supplier can estab-lish a symbiotic relationship and create interwoven processesto acquire resources and fill resource gaps which facilitatesperformance gains exclusive to that relationship (Grant 1991).In building a theoretical model grounded in the relationalview, we focused on GSI as it is becoming an increasinglyvaluable source of competitive advantage, enhancing flexibil-ity performance outcomes which then translate into supplychain value (Frazier 1999). By asking managers involved insupply chain operations about their relationship with a keyglobal supplier, we offer more insight about the significanceof the manufacturer–supplier relationship as a vehicle for cre-ating unique capabilities that lead to create ‘‘win-win’’ oppor-tunities for both. Specifically, this study examined therelationships among the drivers of GSI which include bothbehavioral and operational components, and GSI outcomesthat affect the supplier’s flexibility. This represents a signifi-cant contribution to the existing body of knowledge given thelack of empirical studies utilizing the relational view of thefirm in a global supply chain interfirm context.

The first part of the theoretical model addressed the driv-ers of GSI. This research offers more support for the impor-tance of firm’s disposition through examining the influenceof SCO on the firm’s ability to create collaborative behaviorsand coordinating mechanisms and to also directly enableGSI. These dispositions influence how firms behave andinteract in interfirm relationships (Johnson and Sohi 2001),and previous research indicates that they remain fairly con-sistent across situations and over time (Weiss and Adler1984). SCO encompasses those attitudes that create the phi-losophy that establishing common win-win goals with keyglobal suppliers will elevate firm and overall supply chainperformance through greater levels of integration.

The research highlights that there can be a lack of opera-tional coordination, collaboration, and integration betweenmanufacturers and whom they perceived as ‘‘key’’ globalsuppliers. Davis-Sramek et al. (2007) point out that on thecontinuum of exchange, firms can engage with key suppliersthrough frequent buying yet they have no characteristicsfound in relational exchange. Therefore, researchers shouldbe careful to distinguish between supplier relationships thatare strictly volume driven with little coordinated activity andinformation sharing, and those that are truly strategic in nat-ure and create integrative processes. Given the significantrelationship between the integration structures and logisticsand firm performance, this research offers more insight intothe benefits of ‘‘true’’ integration with suppliers.

Finally, this research also addresses another important issuein the global supply chain management literature—effects ofCD and national characteristics on supply chain relationshipsand operating mechanisms. The literature on this issue hasbeen controversial with several recent studies finding signifi-cant or insignificant impact from CD (Farley and Lehmann1994; Bowman et al. 2000; Bolton and Myers 2003; Homburget al. 2005; Myers and Cheung 2008). Thus, these resultsstrengthen the idea that CD (in business contexts) is overshad-owed by other factors (Levitt 1983; Heuer et al. 1999), such as

the nature or orientation of a firm’s strategy. SCO in thisstudy had a strong impact on the level of GSI.

Managerial implications

The study supports the contention that integration resultsfrom both informal behaviors residing in the willingness toshare information and knowledge with suppliers through col-laboration, and also in the operational decisions that facili-tate product flow and movement through operationalcoordination. Therefore, supply chain management strategiesmust interconnect what a company ‘‘thinks’’ or ‘‘should do’’with what a company ‘‘does’’ to facilitate the physical flowsas well as the associated service, information, and financialflows. This would be especially critical in a global environ-ment where risk and rewards lead to significant consequences(good or bad) and as firms take advantage of internationaleconomies of scale, scope, learn from different foreign mar-kets, and identify location specific advantages to exploit costdifferentials in factors of production or the limited availabil-ity of resources (Roth and Morrison 1992).

As Figure 1 indicates, this research also examined the per-formance implications of GSI. Our contention is that GSIshould enable the manufacturer to increase performancethrough first impacting the supplier’s flexibility. In an envi-ronment where demand is changing rapidly, industry charac-teristics are evolving quickly, and companies are facing newchallenges every day, flexibility becomes critical, allowingsuppliers to make changes or adjustments with a minimumamount of time and resources (Carlsson 1989; De Toni andTonchia 2001). In increasingly dynamic environments, thisresearch provides empirical support that manufacturing firmscan experience a higher level flexibility from their overseassuppliers by integrating their supply chain processes. Thus,firms that value flexibility in their operations can adjust theirprocess integration levels to attain the required level of flexi-bility.

When a supplier can respond to both macro and microenvironmental changes, the manufacturer benefits throughmore logistics efficiency and effectiveness. Through greatersupplier flexibility, manufacturers can then focus on utilizingresources to reduce costs and to focus on enhancing effec-tiveness through more consistent delivery, a reduction instockouts, and less damage and errors. These mediation per-formance effects also provide more understanding about therole of integration in enhancing firm performance. Bothlogistics efficiency and effectiveness had a positive impact onfirm performance. Therefore, we find more evidence of theimportance of these intermediate performance outcomes as‘‘routes’’ to firm performance, where integration is critical inthis ‘‘chain of events’’ (Vickery et al. 2003).

Another managerial contribution relates to the nature ofSCO within the firm. SCO is referred to as a ‘‘mindset,’’ a‘‘philosophy,’’ and an ‘‘organizational culture.’’ Conceptu-ally, this is consistent with an overall orientation of a firmwith all of its supply chain counterparts. While the conceptdoes represent a philosophy that a company adopts to man-age its supply chain, this does not necessarily mean that thecompany uses this orientation with all of its suppliers and ⁄or

138 A. Omar et al.

customers. Companies may apply the 80–20 rule or othermethods to segment and indentify the important and criticalsuppliers and ⁄or customers and implement this orientationaccordingly. An example of this would be when a companyhas a partnership and strategic relationship with one supplierwhile dealing with others on a transactional ⁄ arms-lengthbasis. Doing business with a ‘‘key’’ supplier may also meanfrequent transactions yet the structure and governance of atransactional (rather than relational) orientation (see Davis-Sramek et al. 2007). So despite the fact that SCO relates to afirm’s mindset, this mindset could be directed to one segmentof the company’s supply chain.

The lack of findings regarding the influence of nationalcultural characteristics in this research may indicate that in aB2B context, more emphasis should be placed on the com-patibility and similarity of corporate cultures as opposed tonational culture. Supply chain managers involved in globaloperations may be able to engage better and establish betterintegration structures with global suppliers or vendors withsimilar corporate cultures.

CONCLUSIONS AND FUTURE RESEARCH

The study involved the weaknesses associated with cross-sec-tional surveys (Podsakoff et al. 2003), using a single infor-mant per firm to collect perceptual data (Van Bruggen et al.2002), and it is also marked with the constraints of the depthof information a survey can capture. One drawback of usinga cross-sectional survey is that investigation of supply chainbehavioral dimensions across global players is limited to apoint-in-time assessment. Future research should be directedtoward longitudinal studies that can capture those behavioralelements, in the context of global operations, over anextended period of time. This could paint a clearer pictureon the effects of behavioral elements on global supply chainoperations and its performance implications.

Perceptual versus actual behavioral data were used to testthe hypotheses. Informants reported perceptions of their expe-riences working with providers. While we mitigated potential

bias in the accuracy of the responses by qualifying informantsand asking them about their level of their confidence in theiranswers, perceptual data are still dependent upon respondents’ability and willingness to mentally retrieve and accuratelyreport on their mental evaluation. Future research would ben-efit from obtaining company data that track coordinationmechanisms set in place, collaboration efforts that are docu-mented, or other relevant data. Finally, we assessed percep-tions of the relationship from only the manufacturer’s frameof reference, and we examined supplier flexibility throughmanufacturer’s observation as well. The next step to investi-gate this theory would be to include the supplier’s assessmentof the relationship, thereby examining dyadic data to increaseour understanding of the relationship.

Direct extensions of this research might incorporate differ-ent contexts or the perceptions of other firms in the supplychain for example: retailers, suppliers, or manufacturingfirms in other geographic regions such as Latin America,Europe, or Asia. Also relevant in the global context wouldbe the service providers such as transportation companies,customs brokerages, expediters, etc. This is particularlyimportant to gain more understanding of the effects ofnational characteristics and CD in the context of global sup-ply chain operations. Research on this topic has been contro-versial (Bowman et al. 2000; Bolton and Myers 2003; Myersand Cheung 2008). Findings from this research did not sup-port the hypothesis that CD plays a role in moderating therelationship between SCO and collaboration or operationalcoordination. More research is warranted in this area giventhe trend of globalization of supply chains and the criticalityof understanding how to manage global operations, takingfactors such as culture distance into consideration.

ACKNOWLEDGMENT

The first three authors dedicate this research to their latecoauthor, Dr. John T. (Tom) Mentzer. The authorsacknowledge Lockheed Martin Corporation for supportingthis research.

APPENDIX

Table A1: Cultural distance dimensions and values

Power

distance Individualism Masculinity

Uncertainty

avoidance

Long term

orientation

Cultural

distance*

USA 40.00 91.00 62.00 46.00 29.00 0.00000Australia 36.00 90.00 61.00 51.00 31.00 0.01733Austria 11.00 55.00 79.00 70.00 N ⁄A 1.25328Bolivia 72.00 14.00 50.00 80.00 N ⁄A 3.22190Brazil 69.00 38.00 49.00 76.00 65.00 1.87586Canada 39.00 80.00 52.00 48.00 23.00 0.11238China 80.00 20.00 66.00 30.00 118.00 2.69878Denmark 18.00 74.00 16.00 23.00 N ⁄A 1.87848Ecuador 78.00 8.00 63.00 67.00 N ⁄A 3.39763

Continued.

Orientation, Coordination, and Flexibility in Global Supply Chains 139

Table A1: (Continued)

Power

distance Individualism Masculinity

Uncertainty

avoidance

Long term

orientation

Cultural

distance*

Finland 33.00 63.00 26.00 59.00 N ⁄A 1.21813France 68.00 71.00 43.00 86.00 N ⁄A 1.32712Germany 35.00 67.00 66.00 65.00 31.00 0.37830Greece 60.00 35.00 57.00 112.00 N ⁄A 3.04646India 77.00 48.00 56.00 40.00 61.00 1.31575Indonesia 78.00 14.00 46.00 48.00 N ⁄A 3.02909Ireland 28.00 70.00 68.00 35.00 N ⁄A 0.29785Israel 13.00 54.00 47.00 81.00 N ⁄A 1.44146Italy 50.00 76.00 70.00 75.00 N ⁄A 0.49108Japan 54.00 46.00 95.00 92.00 80.00 2.36482Kazakhstan 93.00 39.00 36.00 95.00 N ⁄A 3.56439Malaysia 104.00 26.00 50.00 36.00 N ⁄A 3.45971Mexico 81.00 30.00 69.00 82.00 N ⁄A 2.65029Netherlands 38.00 80.00 14.00 53.00 44.00 1.55000Poland 68.00 60.00 64.00 93.00 32.00 1.54406Portugal 63.00 27.00 31.00 3.58 N ⁄A 3.08905Russia 93.00 39.00 36.00 95.00 N ⁄A 3.56439S. Korea 60.00 18.00 39.00 85.00 75.00 3.11916Spain 57.00 51.00 42.00 86.00 N ⁄A 1.60084Sweden 31.00 71.00 5.00 29.00 23.00 2.38894Switzerland 34.00 68.00 70.00 58.00 N ⁄A 0.31279Taiwan 80.00 20.00 66.00 30.00 118.00 2.69878Thailand 64.00 20.00 34.00 64.00 56.00 2.78907UK 35.00 89.00 66.00 35.00 25.00 0.06869Venezuela 81.00 12.00 73.00 76.00 N ⁄A 3.50378

*The cultural distance values were calculated using the Kogut and Singh (1988) formula based on the first four dimensions sincethe fifth dimension was missing several values.

REFERENCES

Anderson, J., and Gerbing, D. 1982. ‘‘Some Methods forRe-Specifying Measurement Models to Obtain Unidimen-sional Construct Measurement.’’ Journal of MarketingResearch 19(4):453–60.

Avittathur, B., and Swamidass, P. 2007. ‘‘Matching PlantFlexibility and Supplier Flexibility: Lessons From SmallSuppliers of U.S. Manufacturing Plants in India.’’ Journalof Operations Management 25(3):717–35.

Azadegan, A., and Dooley, K. 2010. ‘‘Supplier Innovative-ness, Organizational Learning Styles and ManufacturerPerformance: An Empirical Assessment.’’ Journal of Oper-ations Management 28(6):488–505.

Bolton, R., and Myers, M. 2003. ‘‘Price-Based Global Mar-ket Segmentation for Services.’’ Journal of Marketing67(3):108–28.

Bowman, D., Farley, J., and Schmittlein, D. 2000. ‘‘Cross-National Empirical Generalization in Business ServicesBuying Behavior.’’ Journal of International Business Stud-ies 31(4):667–85.

Bucklin, L., and Sengupta, S. 1993. ‘‘Organizing SuccessfulCo-Marketing Alliances.’’ Journal of Marketing 57(2):32–46.

Cagliano, R., Caniato, F., and Spina, G. 2006. ‘‘The LinkageBetween Supply Chain Integration and ManufacturingImprovement Programmes.’’ International Journal ofOperations and Production Management 26(3):282–99.

Cannon, J., Doney, P., Mullen, M., and Petersen, K. 2010.‘‘Building Long-Term Orientation in Buyer-Supplier Rela-tionships: The Moderating Role of Culture.’’ Journal ofOperations Management 28(6):505–21.

Carey, S., Lawson, B., and Krause, D. 2011. ‘‘Social CapitalConfiguration, Legal Bonds and Performance in Buyer-Seller Relationships.’’ Journal of Operations Management29(4):277–88.

Carlsson, B. 1989. ‘‘Flexibility and the Theory of the Firm.’’International Journal of Industrial Organization 7(2):179–203.

Chen, H., Daugherty, P., and Landry, T. 2009a. ‘‘SupplyChain Process Integration: A Theoretical Framework.’’Journal of Business Logistics 30(2):27–46.

Chen, H., Daugherty, P., and Roath, T. 2009b. ‘‘Definingand Operationalizing Supply Chain Process Integration.’’Journal of Business Logistics 30(1):63–84.

Cheung, M.-S., Myers, M., and Mentzer, J. 2010. ‘‘DoesRelationship Learning Lead to Relationship Value? A

140 A. Omar et al.

Cross-National Supply Chain Investigation.’’ Journal ofOperations Management 28(6):472–87.

Christopher, M. 2000. ‘‘The Agile Supply Chain.’’ IndustrialMarketing Management 29(1):37–44.

Cousins, P., and Menguc, B. 2006. ‘‘The Implications ofSocialization and Integration in Supply Chain Manage-ment.’’ Journal of Operations Management 24(5):604–20.

Damanpour, F., and Gopalakrishnan, S. 2001. ‘‘TheDynamics of the Adoption of Product and Process Inno-vations in Organizations.’’ Journal of Management Studies38(1):45–65.

Das, T., and Teng, B. 2000. ‘‘Resource-Based Theory of Stra-tegic Alliances.’’ Journal of Management 26(1):31–62.

Daugherty, P., Richey, R., Roath, A., Min, S., Chen, H.,Arndt, A.D., and Genchev, S.E. 2006. ‘‘Is CollaborationPaying Off for Firms?’’ Business Horizons 49:61–70.

Davis-Sramek, B., Fugate, B., and Omar, A. 2007. ‘‘Func-tional ⁄Dysfunctional Supply Chain Exchanges.’’ Interna-tional Journal of Logistics and Physical DistributionManagement 37(1):43–63.

De Toni, A., and Tonchia, S. 2001. ‘‘Definitions and Link-ages Between Operational and Strategic Flexibilities.’’Omega 33(6):525–40.

Dillman, D. 2000. Mail and Internet Surveys: The TailoredDesign Method. New York: John Wiley & Sons.

Doney, P., and Cannon, J. 1997. ‘‘An Examination of theNature of Trust in Buyer-Seller Relationships.’’ Journal ofMarketing 61:35–51.

Droge, C., Jayaram, J., and Vickery, S. 2004. ‘‘The Effectsof Internal Versus External Integration Practices onTime-Based Performance and Overall Firm Performance.’’Journal of Operations Management 22(6):557–73.

Dwyer, F., Schurr, P., and Oh, S. 1987. ‘‘Developing Buyer-Seller Relationships.’’ Journal of Marketing 51(2):11–27.

Dyer, J., and Singh, H. 1998. ‘‘The Relational View: Cooper-ative Strategy and Sources of Interorganizational Compet-itive Advantage.’’ Academy of Management Review23(4):660–79.

Ellinger, A., Daugherty, P., and Keller, S. 2000. ‘‘The Rela-tionship Between Marketing ⁄Logistics InterdepartmentalIntegration and Performance in U.S. ManufacturingFirms: An Empirical Study.’’ Journal of Business Logistics65(4):82–105.

Ellinger, A.E., Ellinger, A.D., and Keller, S. 2002. ‘‘LogisticsManagers’ Learning Environments and Firm Perfor-mance.’’ Journal of Business Logistics 23(1):19–37.

Eltantawy, R., Giunipero, L., and Fox, G. 2009. ‘‘A Strate-gic Skill Based Model of Supplier Integration and ItsEffect on Supply Management Performance.’’ IndustrialMarketing Management 38(8):925–36.

Farley, J., and Lehmann, D. 1994. ‘‘Cross-National ‘Laws’and Differences in Market Response.’’ Management Sci-ence 40(1):111–22.

Fornell, C., and Larcker, D. 1981. ‘‘Evaluating StructuralEquation Models With Unobservable Variables and Mea-surement Error.’’ Journal of Marketing Research 18(1):39–50.

Forslund, H., and Jonsson, P. 2009. ‘‘Obstacles to SupplyChain Integration of the Performance Management Pro-

cess in Buyer-Supplier Dyads: The Buyers’ Perspective.’’International Journal of Operations and Production Man-agement 29(1):77.

Frazier, G. 1999. ‘‘Organizing and Managing Channels ofDistribution.’’ Journal of the Academy of Marketing Sci-ence 27(2):226–40.

Frazier, G., Spekman, R., and O’Neal, C. 1988. ‘‘Just-in-Time Exchange Relationships in Industrial Markets.’’Journal of Marketing 52(4):52–67.

Frohlich, M., and Westbrook, R. 2001. ‘‘Arcs of Integration:An International Study of Supply Chain Strategies.’’ Jour-nal of Operations Management 19(2):185–200.

Fugate, B., Sahin, F., and Mentzer, J. 2006. ‘‘Supply ChainManagement Coordination Mechanisms.’’ Journal of Busi-ness Logistics 27(2):129–61.

Fugate, B., Stank, T., and Mentzer, J. 2009. ‘‘LinkingImproved Knowledge Management to Operational andOrganizational Performance.’’ Journal of Operations Man-agement 27(3):247–64.

Garver, M., and Mentzer, J. 1999. ‘‘Logistics ResearchMethods: Employing Structural Equation Modeling toTest for Construct Validity.’’ Journal of Business Logistics20(1):33–57.

Grant, R. 1991. ‘‘The Resource-Based Theory of Competi-tive Advantage: Implications for Strategy Formulation.’’California Management Review 33(3):114–35.

Green, K., and Inman, R. 2005. ‘‘Using a Just-in-Time Sell-ing Strategy to Strengthen Supply Chain Linkages.’’ Inter-national Journal of Production Research 43(16):3437–53.

Griffith, D., and Myers, M. 2005. ‘‘The Performance Impli-cations of Strategic Fit of Relational Norm GovernanceStrategies in Global Supply Chain Relationships.’’ Journalof International Business Studies 36:254–69.

Handfield, R., Ragatz, G., Petersen, K., and Monczka, R.1999. ‘‘Involving Suppliers in New Product Develop-ment.’’ California Management Review 42(1):59–84.

Heuer, M., Cummings, J., and Hutabarat, W. 1999. ‘‘CulturalStability or Change Among Managers in Indonesia?’’ Jour-nal of International Business Studies 30(3):599–610.

Hofstede, G. 1980. Culture’s Consequences: International Dif-ferences in Work-Related Values. Beverly Hills, CA: SagePublications.

Hofstede, G. 2001. Culture’s Consequences: Comparing Val-ues, Behaviors, Institutions and Organizations AcrossNations. 2nd ed. Thousand Oaks, CA: Sage.

Homburg, C., Kuester, S., Beutin, N., and Menon, A. 2005.‘‘Determinants of Customer Benefits in Business-to-Busi-ness Markets: A Cross-Cultural Comparison.’’ Journal ofInternational Marketing 13(3):1–31.

Hult, G., Ketchen, D., Adams, G., and Mena, J. 2008. ‘‘Sup-ply Chain Orientation and Balanced Scorecard Perfor-mance.’’ Journal of Managerial Issues 20(4):526–44.

Hutzschenreuter, T., and Voll, J. 2008. ‘‘Performance Effectsof Added Cultural Distance in the Path of InternationalExpansion: The Case of German Multinational Enter-prises.’’ Journal of International Business Studies 39(1):53–70.

Jap, S. 2001. ‘‘Pie-Sharing in Complex Contexts.’’ Journal ofMarketing Research 38(1):86–99.

Orientation, Coordination, and Flexibility in Global Supply Chains 141

Jaworski, B., and Kohli, A. 1993. ‘‘Market Orientation:Antecedents and Consequences.’’ Journal of Marketing57(3):53–70.

Johnson, J., and Sohi, R. 2001. ‘‘The Influence of Firm Pre-dispositions on Interfirm Relationship Formation in Busi-ness Markets.’’ International Journal of Research inMarketing 18(4):299–318.

Kannan, V., and Tan, K. 2006. ‘‘The Impact of Supplier Selec-tion and Buyer-Supplier Engagement on Relationship andFirm Performance.’’ International Journal of Physical Dis-tribution and Logistics Management 36(10):755–75.

Khazanchi, S., Lewis, M., and Boyer, K. 2007. ‘‘Innovation-Supportive Culture: The Impact of Organizational Valueson Process Innovation.’’ Journal of Operations Manage-ment 25(4):871–84.

Kim, W. 2009. ‘‘An Investigation on the Direct and IndirectEffect of Supply Chain Integration on Firm Perfor-mance.’’ International Journal of Production Economics119(2):328–46.

Kogut, B., and Singh, H. 1988. ‘‘The Effect of National Cul-ture on the Choice of Entry Mode.’’ Journal of Interna-tional Business Studies 19(3):411–32.

Kotabe, M., and Murray, J. 2004. ‘‘Global Sourcing Strategyand Sustainable Competitive Advantage.’’ Industrial Mar-keting Management 33(1):7–8.

Koufteros, X., Cheng, E., and Kee-hung, L. 2007. ‘‘Black-box’’ and ‘‘Gray-box’’ Supplier Integration in ProductDevelopment: Antecedents, Consequences and the Moder-ating Role of Firm Size.’’ Journal of Operations Manage-ment 25(4):847–70.

Krajewski, L., Wei, J., and Tang, L. 2005. ‘‘Responding toSchedule Changes in Build-to-Order Supply Chains.’’Journal of Operations Management 23(5):452–69.

Kumar, V., Fantazy, K., Kumar, U., and Boyle, T. 2006.‘‘Implementation and Management Framework for Sup-ply Chain Flexibility.’’ Journal of Enterprise InformationManagement 19(3):303–19.

Kumar, S., and Kopitzke, K. 2008. ‘‘A Practitioner’s Deci-sion Model for the Total Cost of Outsourcing and Appli-cation to China, Mexico and the United States.’’ Journalof Business Logistics 29(2):107–39.

Leung, K., Bhagat, R., Buchan, N., Erez, M., and Gibson,C. 2005. ‘‘Culture and International Business: RecentAdvances and Their Implications for Future Research.’’Journal of International Business Studies 36(4):357–78.

Levitt, T. 1983. ‘‘The Globalization of Markets.’’ HarvardBusiness Review 61(3):92–102.

Mackinnon, D., Lockwood, C., Hoffman, J., West, S., andSheets, V. 2002. ‘‘A Comparison of Methods to TestMediation and Other Intervening Variable Effects.’’ Psy-chological Methods 7(1):83–104.

Manuj, I., and Mentzer, J. 2008. ‘‘Global Supply Chain RiskManagement.’’ Journal of Business Logistics 29(1):133–55.

Mentzer, J., DeWitt, W., Keebler, J., Min, S., Nix, N.,Smith, C., and Zacharia, Z. 2001. ‘‘Defining SupplyChain Management.’’ Journal of Business Logistics22(2):1–25.

Mentzer, J., and Flint, D. 1997. ‘‘Validity in LogisticsResearch.’’ Journal of Business Logistics 18(1):199–216.

Mentzer, J., and Konrad, B. 1991. ‘‘An Efficiency ⁄Effective-ness Approach to Logistics Performance Analysis.’’ Jour-nal of Business Logistics 12(1):33–61.

Metcalf, L., Frear, C., and Krishnan, R. 1992. ‘‘Buyer-SellerRelationships: An Application of the IMP InteractionModel.’’ European Journal of Marketing 26(2):27–46.

Min, S., Mentzer, J., and Ladd, R. 2007. ‘‘A Market Orienta-tion in Supply Chain Management.’’ Journal of Academyof Marketing Science 35(4):507–22.

Moorman, C., Deshpande, R., and Zaltman, G. 1993. ‘‘Fac-tors Affecting Trust in Market Research Relationships.’’Journal of Marketing 57(1):81–101.

Morgan, R., and Hunt, S. 1994. ‘‘The Commitment-TrustTheory of Relationship Marketing.’’ Journal of Marketing58(3):20–38.

Myers, M., and Cheung, M.-S. 2008. ‘‘Sharing Global Sup-ply Chain Knowledge.’’ Sloan Management Review 49(4):67–74.

Nakata, C., and Sivakumar, K. 1996. ‘‘National Culture andNew Product Development: An Integrative Review.’’Journal of Marketing 60(1):61–72.

Narasimhan, R., and Das, A. 2001. ‘‘The Impact of Purchas-ing Integration and Practices on Manufacturing Perfor-mance.’’ Journal of Operations Management 19(5):593–609.

Pagell, M. 2004. ‘‘Understanding the Factors That Enableand Inhibit the Integration of Operations, Purchasing andLogistics.’’ Journal of Operations Management 22(5):459–87.

Paulraj, A., and Chen, I. 2007. ‘‘Environmental Uncertaintyand Strategic Supply Management: A Resource Depen-dence Perspective and Performance Implications.’’ Journalof Supply Chain Management 43(3):29–42.

Petersen, K., Handfield, R., and Ragatz, G. 2005a. ‘‘SupplierIntegration Into New Product Development: Coordinat-ing Product, Process and Supply Chain Design.’’ Journalof Operations Management 23(3 ⁄ 4):371–88.

Petersen, K., Handfield, R., and Monczka, R. 2005b. ‘‘AnExamination of Collaborative Planning Effectiveness andSupply Chain Performance.’’ Journal of Supply ChainManagement: A Global Review of Purchasing and Supply41(2):14–25.

Podsakoff, P., MacKenzie, S., Jeong Yeon, L., andPodsakoff, N. 2003. ‘‘Common Method Biases in Behav-ioral Research: A Critical Review of the Literature andRecommended Remedies.’’ Journal of Applied Psychology88(5):879–903.

Prior, D. 2006. ‘‘Integrating Stakeholder Management andRelationship Management: Contributions From the Rela-tional View of the Firm.’’ Journal of General Management32(2):17–30.

Ragatz, G., Handfield, R., and Petersen, K. 2002. ‘‘BenefitsAssociated With Supplier Integration Into New ProductDevelopment Under Conditions of Technology Uncer-tainty.’’ Journal of Business Research 55(5):389–400.

Ragatz, G., Handfield, R., and Scannell, T. 1997. ‘‘SuccessFactors for Integrating Suppliers Into New ProductDevelopment.’’ The Journal of Product Innovation Man-agement 14(3):190–202.

142 A. Omar et al.

Roath, A., Miller, S., and Cavusgil, S. 2002. ‘‘A ConceptualFramework of Relational Governance in Foreign Distrib-utor Relationships.’’ International Business Review11(1):1–15.

Rodrigues, A., Stank, T., and Lynch, D. 2004. ‘‘LinkingStrategy, Structure, Process, and Performance in Inte-grated Logistics.’’ Journal of Business Logistics 25(2):65–94.

Romano, P. 2003. ‘‘Coordination and Integration Mecha-nisms to Manage Logistics Processes Across Supply Net-work.’’ Journal of Purchasing and Supply Management 9:119–34.

Roth, K., and Morrison, A. 1992. ‘‘Business-Level Competi-tive Strategy: A Contingency Link to Internationaliza-tion.’’ Journal of Management 18(3):473–87.

Sahin, F., and Robinson, P. 2002. ‘‘Flow Coordination andInformation Sharing in Supply Chains: Review, Implica-tions, and Direction for Future Research.’’ Decision Sci-ences 33(4):505–36.

Sanchez-Rodriguez, C. 2009. ‘‘Effect of Strategic Purchasingon Supplier Development and Performance: A StructuralModel.’’ Journal of Business and Industrial Marketing24(3 ⁄4):161–72.

Selnes, F., and Sallis, J. 2003. ‘‘Promoting RelationshipLearning.’’ Journal of Marketing 67(3):80–95.

Shoenherr, T. 2009. ‘‘Logistics and Supply Chain Manage-ment Applications Within a Global Context: An Over-view.’’ Journal of Business Logistics 30(2):1–26.

Siguaw, J., Simpson, P., and Baker, T. 1998. ‘‘Effects of Sup-plier Market Orientation on Distributor Market Orienta-tion and the Channel Relationship: The DistributorPerspective.’’ Journal of Marketing 62(3):99–111.

Sobel, M. 1982. ‘‘Asymptotic Confidence Intervals for Indi-rect Effects in Structural Equations Models.’’In Sociologi-cal Methodology, edited by S. Leinhart, 290–312. SanFrancisco, CA: Jossey-Bass.

Stank, T., Daugherty, P., and Ellinger, A. 1999. ‘‘Market-ing ⁄Logistics Integration and Firm Performance.’’ Inter-national Journal of Logistics Management 10(1):11–24.

Stank, T., Keller, S., and Daugherty, P. 2001. ‘‘Supply ChainCollaboration and Logistical Service Performance.’’ Jour-nal of Business Logistics 22(1):29–48.

Stevenson, M., and Spring, M. 2009. ‘‘Supply Chain Flexibil-ity: An Inter-Firm Empirical Study.’’ International Journalof Operations and Production Management 29(9):946–71.

Stock, G., Greis, N., and Kasarda, J. 1999. ‘‘Logistics Strat-egy and Structure: A Conceptual Framework.’’ Interna-tional Journal of Physical Distribution and LogisticsManagement 29(4):224–39.

Swafford, P., Ghosh, S., and Murthy, N. 2008. ‘‘AchievingSupply Chain Agility Through IT Integration and Flexi-bility.’’ International Journal of Production Economics116(2):288–97.

Swink, M., Narasimhan, R., and Wang, C. 2007. ‘‘ManagingBeyond the Factory Walls: Effects of Four Types ofStrategic Integration on Manufacturing Plant Performance.’’Journal of Operations Management 25(1):148–64.

Tan, K., Kannan, V., Handfield, R., and Ghosh, S. 1999.‘‘Supply Chain Management: An Empirical Study of Its

Impact on Performance.’’ International Journal of Opera-tions and Production Management 19(10):1034–52.

Tracey, M. 2004. ‘‘A Holistic Approach to New ProductDevelopment: New Insights.’’ Journal of Supply ChainManagement 40(4):37–55.

Upton, D. 1995. ‘‘What Really Makes Factories Flexible?’’Harvard Business Review 73(4):74–84.

Van Bruggen, G., Lilien, G., and Kacker, M. 2002. ‘‘Infor-mants in Organizational Marketing Research: Why UseMultiple Informants and How to Aggregate Responses.’’Journal of Marketing Research 39(4):469–78.

Vickery, S., Jayaram, J., Droge, C., and Calantone, R. 2003.‘‘The Effects of an Integrative Supply Chain Strategy onCustomer Service and Financial Performance: An Analy-sis of Direct Versus Indirect Relationships.’’ Journal ofOperations Management 21(5):523–39.

Wagner, S. 2003. ‘‘Intensity and Managerial Scope of Sup-plier Integration.’’ Journal of Supply Chain Management:A Global Review of Purchasing and Supply 39(4):4–15.

Wagner, S. 2006. ‘‘A Firm’s Responses to Deficient Suppliersand Competitive Advantage.’’ Journal of BusinessResearch 59(6):686–95.

Weiss, H. M., and Adler, S. 1984. ‘‘Personality and organiza-tional behavior.’’ In Research in Organizational Behavior,edited by B.M. Staw and L.L. Cummings, Vol. 6. Green-wich, CT: JAI Press.

Wisner, J. 2003. ‘‘A Structural Equation Model of SupplyChain Management Strategies and Firm Performance.’’Journal of Business Logistics 24(1):1–26.

Zacharia, Z., Nix, N., and Lusch, R. 2009. ‘‘An Analysis ofSupply Chain Collaborations and Their Effect on Perfor-mance.’’ Journal of Business Logistics 30(2):101–24.

Zailani, S., and Rajagopal, P. 2005. ‘‘Supply Chain Integra-tion and Performance: US Versus East Asian Compa-nies.’’ Supply Chain Management 10(5):379–93.

Zhang, C., Cavusgil, S., and Roath, A. 2003. ‘‘ManufacturerGovernance of Foreign Distributor Relationships: Do Rela-tional Norms Enhance Competitiveness in the Export Mar-ket?’’ Journal of International Business Studies 34(6):550–66.

SHORT BIOGRAPHIES

Ayman Omar (PhD University of Tennessee) is an Assis-tant Professor and Marvin Fair Faculty Fellow at the KogodSchool of Business at American University. His researchinterests target different aspects of global supply chain man-agement. Primarily, his focus is on drivers and outcomes ofglobal supply chain integration with an emphasis on supplychain flexibility. In addition, Dr. Omar’s research interestsinclude global supply chain sustainability, and global supplychain risk management. He has published in the Journal ofBusiness Logistics, International Journal of Physical Distribu-tion, and Logistics Management. He has worked for severalyears in the oil industry in Europe and Northern Africa andhas consulted for numerous multinational, public, and pri-vate corporations.

Beth Davis-Sramek (PhD University of Tennessee) is anAssistant Professor in the Department of Marketing at the

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University of Louisville. Her research interests include therole of logistics in supply chain management, the impact oflogistics service in developing customer loyalty, and the stra-tegic role of logistics in creating competitive advantage. Shehas published articles appearing in the Journal of the Acad-emy of Marketing Science, Journal of Operations Manage-ment, Journal of Business Logistics, International Journal ofPhysical Distribution and Logistics Management, and Interna-tional Journal of Logistics Management. She previouslyworked in the services industry in both product developmentand service operations.

Matthew B. Myers (PhD Michigan State University) is theNestle Professor and Associate Dean of Executive Education

at the University of Tennessee. Dr. Myers’ primary areas ofresearch are in global supply chain networks, foreign marketentry strategies, and comparative marketing systems. Hisresearch has been published or is forthcoming in a numberof outlets including the Strategic Management Journal, Jour-nal of Marketing, Journal of Operations Management, Journalof International Business Studies, Journal of the Academy ofMarketing Science, and Sloan Management Review. He isalso coeditor of the Handbook of Global Supply Chain Man-agement (Sage). He has studied, taught, and worked in Cen-tral America, South America, Europe, Central and EastAsia, and has acted as a consultant to organizations in theglobal distribution, chemical, insurance, pharmaceutical, andmarketing research industries.

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