assessing effectiveness of supply chain collaboration: …€¦ · sharing information, joint...

Introduction

A traditional arms-length approachto business partnership is not anacceptable or effective approach inthe present forceful and aggressiveglobal business environment(Bowersox et al., 2000). Innovativestrategies are required to create acompetitive advantage that allowsfor cost reductions, revenueenhancements, and flexibility whendealing with financial uncertainties.Supply chain management presentsthat opportunity throughcollaborative relationships thatmaximize desired service levels,minimize costs, and generatebenefits to customers (Bowersox et al.,

2000; Mentzer et al., 2001). Severalcross-sectional studies havereported that higher levels ofcollaboration tend to provide acompetitive advantage to the firmsin the supply chain (Heikkila, 2002;Sandberg, 2007; Sheu et al., 2006;Simatupang & Sridharan, 2005;Singh & Power, 2009; Vickery et al.,2003; Zacharia et al., 2009).

Supply chain (SC) collaboration isdefined as “a win/win arrangementthat is likely to provide improvedbusiness success for both parties”(McClellan, 2002, p. 20). Since theearly 1990s, collaboration has been gaining impetus in theorganizational context and is seen

Even though collaboration has obtained increasing popularity in thesupply chain (SC) arena, its effectiveness has not been measuredempirically at a national level. In this paper, we refine, validate, and thenemploy an instrument that measures (1) the extent of informationsharing, joint planning, goal congruence, personal interaction, and trustbetween SC partners and (2) manager perception of the effectiveness ofthis collaborative relationship. These factors along with several firm-specific variables that the literature has suggested (i.e., number ofemployees, annual sales revenue, percent of partners involved incollaboration, years in collaboration, and length of current agreement)are used to explain the effectiveness of SC collaboration using regressionanalysis. Our research points out that larger firms (measured by sales revenue andthe number of employees) and firms that collaborate extensively tend tovalue the effectiveness of collaboration more highly. Interestingly, wecould not confirm a link between perceived effectiveness and length ofexperience with collaborative SC efforts. Second, after adjusting forsignificant firm-specific effects, our results confirm that extensivelysharing information, joint planning, and using information systemscollaboratively tend to increase the perceived value of collaboration.Finally, although goal congruence was linked to collaborationeffectiveness, personal interaction and trust were not found to bestatistically significant.

Assessing Effectiveness of Supply ChainCollaboration: An Empirical Study

2Supply Chain Forum An International Journal Vol. 11 - N°2 - 2010 www.supplychain-forum.com

Amarpreet S. Kohli University of Southern Maine

[email protected].

John B. Jensen University of South Carolina

as a vital element and major forcebehind improving SC performance(Ellram & Cooper, 1990).Collaboration entails organizationsworking together to achieve mutual benefits. It looks beyond simple coordination by sharinginformation, participating incollaborative activities, managingexceptions, determining demandallocations, and monitoringperformance goals (Chen & Paulraj,2004; Daugherty et al., 2006;Simatupang & Sridharan, 2004).

Several benefits of collaborationhave been documented over theyears for manufacturers, suppliers,and customers. These includeimpressive cost reductions,improved service, improved end-customer satisfaction, shorterlead times, improved informationvisibility, increased competitiveness,and a clearer division ofresponsibility among partners(Akintoye et al., 2000; Matopouloset al., 2007; Sandberg, 2007). Barriers to successfulimplementation of collaboration inthe SC have been identified as fearof failure, exposure to competition,concern about trust, increase ofoperational complexity, andtechnological incompatibilities(Barratt, 2004; Matopoulos et al.,2007, Sandberg, 2007; Van Weele,2009).

Even though SC collaboration hasincreased in popularity, itseffectiveness has not beenmeasured empirically at a nationallevel. Further, although social ortechnical factors have beenobserved to influence successfulcollaborative relationships in theSC, only a handful of studies haveexamined some of these factorsand not all have been studiedtogether. The purpose of this studyis to refine, validate, and employ aninstrument that measures the jointimpact of factors (i.e., informationsharing, joint planning, goalcongruence, personal interaction,and trust) along with firm-specificvariables on the operational andoverall effectiveness of SCcollaboration.

This paper is organized in thefollowing manner. The first section

reviews the previous literature onthe use and effectiveness of SC collaboration in diversebusinesses. Next, a theoreticalfoundation is proposed based onthe existing literature that leads toconstruct development. In thisframework, we posit thateffectiveness of SC collaboration isdriven by information sharing, jointplanning, goal congruence,personal interaction, and trust.Then, the research design and datacollection procedures aredescribed, followed by results.Finally we offer conclusions, withdiscussion of the results, along withsome suggested directions forfuture exploration.

Literature Review

Despite the attention this field hasreceived, SC collaboration researchis still in its infancy. Akintoye et al.(2000) identified improvedproduction planning andpurchasing as key targets for theapplication of SC collaboration inthe United Kingdom constructionindustry. Significant correlationwas observed between externaland internal collaboration (Stank etal., 2001). Integrative mechanisms,shared culture, commitment, trust,and communication were identifiedas pre-conditions for learning,which had positive impact on SCperformance measures (Spekmanet al., 2002). Skjoett-Larsen et al.(2003) asserted that companiesneeded confidence and trust ineach other to initiate collaboration.Lejeune and Yakova (2005)concluded that interdependencewas central to SC performancebecause it allowed firms to havecompetitive advantage over others.

Research on collaboration in thesoftware industry indicated thatfirms that collaborate need notshare risks. However, firms thatscored high on shared risk-takingtended to be more profitable than their competitors, butcollaboration alone did notimprove performance (Tucci et al.,2005). Lee (2005) emphasized thatsimulation and empirical researchmethods miss critical communicationpatterns in an SC, and proposed theuse of social network analysis to measure SC collaboration bystudying the quality ofrelationships between members.

Cassivi (2006) surveyed thetelecommunications industry inwhich information visibility wasidentified as a significant element ofcollaboration in maintaining anefficient SC. Social factors such asinterdependence, intensity, andtrust have also been shown to beimportant. Sheu et al. (2006)demonstrated that a lack of socialfactors have a negative impact onpartnership and implementation oftechnical factors (e.g., informationsharing platforms and IT support).A study conducted by Vlachos and Bourlakis (2006) revealedcontrasting views on collaborationbetween food SC members.Retailers regarded factors ofcommitment, information sharing,category management, andphysical distribution as critical fora successful relationship, whereasmanufacturers regarded trust to beinstrumental in relationshipbuilding. The volatile nature of theproducts has also been observed toimpinge on the trust-buildingprocess and hinder theestablishment of SC relationshipsin the food industry (Matopoulos et al., 2007). Sandberg (2007)established a clear relationshipbetween the intensity ofcollaboration and positive effectsexperienced from thecollaboration.

Soosay et al. (2008) reported thatthe ability of managers to workwith partners enables the firms tointegrate and link their operations,which increases effectiveness andopportunities for innovation.Several recent studies have also


What are the key

drivers for

effectiveness of

supply chain

collaboration?

highlighted the need to move fromdyadic relationships to informationsharing and relationship buildingwith both customers and suppliers(Evrard-Samuel, 2008; Singh &Power, 2009). Collaborating bysharing resources, operations, andimprovements within the SC wasinstrumental in the financialsuccess of Japanese manufacturers(Nakano, 2009). Actualperformance measures (cost,quality, cycle time, and customervalue) have been observed to bemore critical for improvedperformance than relationship-oriented factors such as increasedcommunication and effectiveworking relationships (Zacharia etal., 2009). Vieira et al. (2009)studied the strategic, tactical, andinterpersonal types ofcollaboration and five keyindicators emerged: (1) jointactions, (2) information sharing, (3)interpersonal integration, (4) gainsand cost sharing, and (5) strategicintegration.

Although the benefits of SCcollaboration have been noted,much of the previous researchfocused on measurements to gaugethe degree or forms ofcollaboration. Little attention hasbeen given to measuring theeffectiveness of collaborationamongst SC partners at a nationallevel (Simatupang & Sridharan,2004). The literature is also fuzzyon what happens when companiescollaborate and what specifically isachieved (Sandberg, 2007). In thenext section, we discuss thetheoretical foundation that guidedinstrument refinement andvalidation as well as data collectionand provide the conceptual andoperational definitions of all thevariables being measured.

Theoretical Foundation andConstruct Development

Past research studies havepredominantly emphasized thesignificance of several factors toimprove the performance of the SC(Daugherty et al., 2006; Lambert &Cooper, 2000; Lau & Lee, 2000).Though more evidence has beenprovided through conceptualframeworks compared to empirical

research in an SC environment (Lee& Whang, 2000), only a handful ofstudies have empirically tested theeffectiveness of collaboration in theSC (Akintoye et al., 2000; Daughertyet al., 2006; Simatupang &Sridharan, 2005; Skjoett-Larsen etal., 2003; Vieira et al., 2009).

Akintoye et al. (2000) developed aninstrument that focused onstudying the relationships betweenupstream and downstream firms inthe construction industry SC.Daugherty et al. (2006) focusedtheir research on formalization ofstrategic collaboration. Simatupangand Sridharan (2005) conducted anempirical study to develop acollaboration index using threeinterrelated dimensions:information sharing, decisionsynchronization, and incentivealignment. However, their studywas focused on companies in NewZealand. Even Skjoett-Larsen et al.(2003) did not study strategic orinterpersonal factors. Vieira et al.(2009) integrated strategic, tactical,and interpersonal factors to assesscollaboration in the SC, but theirresearch was targeted at a retail SCin Brazil. It was evident thatintegration of all these factors instudying the overall andoperational effectiveness of the SCwithin the U.S. context was lackingin the literature. Table 1 provides asummary of key SC collaborationconstructs identified in theliterature.

Measures of Effectiveness

Two constructs (operationaleffectiveness and overalleffectiveness) were identified in theliterature to assess theeffectiveness of SC collaboration.Operational effectiveness (alsoreferred to as efficiency) of SCcollaboration for this study hasbeen defined to be how well theresources of the firm are utilized toreap benefits for all members of theSC. Elements of this measureinclude cost reduction, reducedinventory, reduced lead time, andstreamlining of the SC processes.These components were similar tothose reported by Min et al. (2005).Alternatively, overall effectivenessof SC collaboration has beendefined as the extent to which thejoint goals are measured withregards to improved service level,increased market share, betterpricing, increased sales, newproduct development, andincreased profits (Min et al., 2005).Thus, we employ both elements toform an overall measure of SCeffectiveness.

Elements of Collaboration

Figure 1 provides a pictorialdepiction of the conceptualframework used in this study toassess the effectiveness of SCcollaboration. Based on theliterature, we hypothesize thefollowing five major factors to exert


Table 1Constructs Based on Literature Review

a vital influence on theeffectiveness of SC collaboration:(1) information sharing, (2) jointplanning, (3) goal congruence, (4)personal interactions, and (5) trust.The nature of collaboration ischaracterized by informationsharing, joint planning, jointproblem solving, jointperformance, and leveraging(Daugherty et al., 2006; Min et al.,2005). Antecedents of collaborationare rooted in development of acollaborative relationship. Inaddition, personal interactionsgeared towards trust, commitment,and cooperation allow for opencommunication and informationsharing and joint planning amongSC partners. Data sharing and jointplanning lead to goal congruence,which in turn influencesoperational and overalleffectiveness of collaborationamong SC partners. In line with theliterature, the first set of factors

(information sharing and jointplanning) in our study characterizethe nature of collaboration whereasthe remaining ones (goalcongruence, personal interactions,and trust) act as the contextualmoderators. The following detailsthe conceptual and operationaldefinitions of these factors thatguided the development andvalidation of our refinedinstrument.

Information SharingInformation shared among SCpartners and customers in real-timeand/or in person tend to improvebusiness operations in terms ofspeed, agility, control, andcustomer response by focusing oncommunications, relationships,and knowledge (Manthou et al.,2004; Myers et al., 2000). However,critical information sharing canhappen only if there is confidenceamong SC partners to trust each

other and develop formalguidelines and communicationchannels. Three importantdimensions/variables of informationsharing that were identified in theliterature and subsequently pilottested in our instrument arediscussed below.

- Operations InformationOperational information that isgenerally shared among SCpartners includes demandforecasts, order tracking data,inventory levels, lead-timeinformation, material requirements,and pricing information.Information sharing is an essentialcomponent of routine operationsand also vital for collaborativestrategic planning that helps fulfilldemand more quickly and reducedelivery lead time (Lejeune &Yakova, 2005; Simatupang &Sridharan, 2004). It augmentsproduct and information flowamong SC partners and allowsthem to work together to developjoint business plans (Min et al.,2005). It can be carried out as aformal practice that involvesperiodic meetings or can be doneinformally as needed.

- Marketing InformationMarketing information that isgenerally shared among SCpartners includes new productintroductions, promotionalplanning, market trends data, andcustomer preferences. Instantsharing of market information isnot only deemed necessary butalso perceived as a progressivedevelopment that allows all SCmembers to be on the same page(Mason-Jones & Towill, 1997).However, this requires a culture ofopenness and honesty amongst SCpartners (Spekman et al., 1998).

- Systems of Information SharingWhen sharing operational andmarket information, it is imperativeto develop systems/techniques ofdata sharing that are accepted byall SC members. Techniques suchas electronic data interchange(EDI), data warehouse/data mining,and several web-based applicationsare being used by variousorganizations towards this effect.The use of IT and other


Figure 1Conceptual Framework for Understanding CollaborationEffectiveness in Supply Chains

technological advances providesmomentum for the smooth flow of materials and finishedgoods/services, which in turnimproves visibility (Min et al.,2005). Increased communicationthrough information sharing resultsin improved commitment,cooperation, and has a positiveimpact on the SC (Bowersox et al.,2000; Lee & Whang, 2000). Virtualintegration has also been used toreduce the effects of environmentaluncertainties, allowing supplierresponsiveness and flexibility,which results in cost savings forbuyers (Wang et al., 2006).

Joint PlanningAnother important component ofcollaboration that was driven bythe information shared between SCpartners was identified as jointplanning (Barratt, 2004; Jagdev &Thoben, 2001; Min et al., 2005;Sandberg, 2007; Simatupang &Sridharan; 2005). It is essential totest the strategic fit with intendedSC partners and confirm thecompatibility of the companiesthrough joint planning to developand sustain trustworthyrelationships (Naesens et al., 2007).Decision synchronization, capacityplanning, planning of logistics, andbusiness strategy are some otherterms that have been used in theliterature in place of joint planning.Two major areas in which jointplanning was conducted wereidentified as (1) operations and (2)sales.

- Operations PlanningCoordination and integration ofoperational activities is vital foreffective collaboration. Operationsplanning, which allows forintegration of operations andcapacities of all the playersinvolved, has shown a positiverelationship with collaborationincluding improvement in lead timeand other intangible effects(Sandberg, 2007). However, it isnecessary that all SC partnerscollaboratively prioritize goals andobjectives that meet theirexpectations.

- Sales/Business PlanningJoint planning, which is closelyrelated to information sharing,

starts with the development ofcommon sales/business plans thatrequire volume projections amongother pieces of sensitiveinformation to be shared betweenthe trading partners (Min et al.,2005). Additionally, success of theplanning process in terms ofprofitability depends on theresponsiveness of SC memberstowards meeting customers' needs(Simatupang & Sridharan, 2004).

Goal CongruenceCentral to SC collaboration is thenotion that all trading partnersshare similar value systems andhave congruent goals. Goalcongruence, also calledformalization or incentivealignment, is believed to be anessential element of successfulcollaboration, such as thedevelopment of performancemeasures, joint goals andobjectives, IT standardization,defining roles and responsibilitiesof each partner, formalizing thenature of information shared,alignment of collaborativeschedules, and joint developmentof an implementation plan (Jap,2001; Lejeune & Yakova, 2005; Minet al., 2005). Formal rules andstandards for operating proceduresleads to enhanced performance byeliminating ambiguity, providingfocus, and saving time (Daughertyet al., 2006). Most important, aprerequisite for success in thisprocess has been the activeinvolvement and support of topmanagement officials (Mentzer etal., 2001; Sandberg, 2007).

Personal InteractionsInterdependence among SCmembers is critical to thedevelopment of solidarity.Readiness of trading partners toexert effort in developing long-termrelationships through thecommitment of assets (i.e., time,money, and facilities) and opencommunication has been noted tostrengthen personal interactions(Bensaou & Anderson, 1999; Sheu et al., 2006). Increasedinterdependence prompts awillingness to negotiate functionaltransfer, share key information, andparticipate in joint operational

planning (Heikkila, 2002).Moreover, the historical length of arelationship in terms ofcoordination, participation, andjoint problem solving has beenidentified as an important indicatorof a successful partnership.Specifically, longer relationshipsincrease trust and the commitmenttowards reaching joint goals(Bensaou & Anderson, 1999). Grant(2005) however observed an SCrole-based difference in thatcustomers were less willing toembrace these relationships asreadily as suppliers.

TrustTrust requires belief in the honestyof one's partners and confidencethat the partners will stand by theirword. Specifically, trust in the SCdomain includes the belief thatpartners will fulfill theirobligations, resulting in lower costsfor all associated (Heikkila, 2002;Kwon & Suh, 2005). The literaturesupports that trust affects the long-term stability of an organization.Mutual trust provides a base for SCpartners to share confidential andproprietary financial, strategic, andmarketing information (Petersen etal., 2005). However, building trust isnot easy; it requires commitmentand cooperation to act in anunselfish manner for the greaterbenefits of the SC, rather thanopportunistic thinking on the part of a few members. Fear of opportunism sometimesdiscourages firms from establishingtrust-building practices and risktaking, leading to performancereduction (Tucci et al., 2005).Perrons's (2005) agency-basedmodel of outsourcing decisions inthe SC also supports this thesisbecause reputation and trust didnot play a significant role in thelong-term success of theoutsourcing firm. Handfield andSteininger (2005) further stipulatedthat development of trust in acollaborative SC is valuable butbecoming more costly for SCpartners to sustain.

Firm-Specific Variables

In addition to the interaction of allthe previously mentioned factors,


some additional variables were alsoidentified through literature reviewto have effect on operational andoverall effectiveness of SCcollaboration. Key variables thathave been used in prior studiesinclude (1) number of employees,(2) annual sales revenue, (3)percentage of partners involved incollaboration, (4) years ofcollaboration, and (5) length ofcurrent agreement (Akintoye et al.,2000; Chen & Paulraj, 2004; Kwon &Suh, 2005; Matopoulos et al., 2007;Stank et al., 1999; Vieira et al.,2009). In the next section wedescribe the research design anddata collection procedures.

Research Design and DataCollection

Questionnaire Design

A 21-question survey was designedto assess the effectiveness of SCcollaboration. The first sevenquestions were demographic innature regarding the organizationand respondent profile. Questions 8to 12 dealt with the information onthe collaborative relationshipsfirms shared with their tradingpartner(s). The final section of theinstrument (Questions 13 to 21)probed several factors(independent variables) that theliterature suggests affectoperational and overalleffectiveness of SC collaboration.These questions used an 8-pointLikert scale. Prior to datacollection, the content validity ofthe instrument was established bygrounding it strongly in the existingliterature and conducting a pilottest on business communitymembers located in the State ofMaine.

The three-step continuousimprovement approach based onFlynn et al. (1994) was employed toidentify the constructs. It includesdetermination of Cronbach's alpha,exploratory factor analysis (EFA)using principal component analysis(PCA), and a confirmatory factoranalysis (CFA) to evaluateconstruct validity andunidimensionality. Items thatcontributed least to overall internalconsistency, based on inter-

correlation, were deleted, and thepool of items was reduced.Principal component analysis wasemployed and the number ofconstructs was reduced from 13 to8 (five constructs reflecting natureof collaboration and the other threeacting as contextual moderators).

Sample Design and Data Acquisition

The psychometric properties of theinstrument were tested on anationwide sample using aquantitative cross-sectionalresearch design. Convenient(purposive) sampling strategy wasemployed and the unit of analysiswas professional members of theCouncil of Supply ChainManagement Professionals(CSCMP) in 2009. The research wasapproved by the University ofSouthern Maine's Office ofResearch Compliance and therespondents were guaranteedanonymity.

SurveyMonkey (an Internet-basedprogram) was used to host thesurvey and data were collectedduring a two-month period. Twoweeks after the initial invitationalemail, a thank you and reminderemails were sent to all the potentialrespondents. In total, 253responses were received from thesample size of 3,952, resulting in aninitial response rate of 6.4%. Finally,111 surveys were discarded due toincomplete information, resultingin final sample size of 142 with aneffective response rate of 3.6%. Thelow response rate is typical of web-based surveys becauserespondents were unacquaintedwith the survey and its purposeprior to receiving it. Additionally,many potential respondentsprobably did not receive the surveybecause it might have been filteredas spam (Skjoett-Larsen et al.,2003). After testing thepsychometric properties of theinstrument, principal componentfactor analysis of the correlationmatrix and step-wise regressionwas conducted using the Minitabstatistical analysis softwarepackage.

Results

The progression of analysis beganby using industry responses to ourliterature-generated surveyquestions to form factors that tapthe phenomena contained in ourconceptual framework. Two ofthese factors-operationseffectiveness and overalleffectiveness-were then used asdependent variables in two sets ofsequential regression analyses. Thefirst set of regression analysesindividually evaluated the strengthof the association between our twomeasures of SC collaborationeffectiveness and company firm-specific variables. Next, theresiduals of the dependentvariables remaining from thepreceding step were regressed withthe SC factors used as independentvariables. Tables 2a, 2b, 2c, and 2dprovide a summary of thedescriptive characteristics of theresponding firms and managers.

Factor Development

In this first stage of analysis,exploratory factor analysis wasused to assess the covariation ofsurvey question responses relatedto important SC constructs found inthe literature. Survey questionsprobing the two dimensions of theeffectiveness of collaboration (ourdependent variables) weresubjected to principal componentsanalysis. As seen in Table 3a, thediscriminant validity of these twoconstructs may be assessed asadequate given the significance oftheir components' factor loadings.Additionally, these two constructsmay be regarded as internallyconsistent as measured byCronbach's alpha because theacceptable cutoff of 0.60 wasexceeded in both cases (Nunnally,1978).

Subsequently, the constructs of“operational effectiveness” and“overall effectiveness” werecreated by weighting eachcompany response by the factorloadings provided in Table 3a. InTable 3b, some relevant descriptivestatistics of these two newconstructs are provided. On a scalefrom 0.0 (minimum value recorded)



Table 2cRespondents Profile by Type, Number of Employees, and Annual Sales Revenue

Table 2aRespondent Profile by Industry Type

Table 2bRespondent Profile by Title (Supply Chain/Logistics/Procurement/Operations/Other Areas)

to 21.31 (maximum valuerecorded), mean operationalefficiency was found to be 12.55.Further, companies recording ascore of 0.0 to 9.08 fall into thebottom quartile with the topquartile defined by a score between16.70 and 21.31. Likewise, the meanscore on the overall effectivenessscale was calculated as 19.38.Scores ranging from 0.0 to 15.53comprise the bottom quartile, andscores of 24.51 to 28.74 comprisethe top quartile.

Next, the survey responses toquestions suggested by theliterature to tap individualconstructs describing the natureand the extent of SC collaborativerelationships were subjected toprincipal components analysis. Asseen in Table 3c, operations andmarketing information, thecollaborative use of informationtechnology (systems), as well asjoint operations and sales planning,which are factors describing natureof collaboration, emerge asinternally consistent. The table alsodisplays the factor loadings of eachsurvey item that makes asignificant contribution (loading of0.60 or higher) to each of the fiveconstructs. Additionally, evidenceof internal consistency is displayedin the form of the Eigen values and

Cronbach's alphas for eachconstruct.

Finally, the constructs for threecontextual moderators of theeffectiveness of SC collaborationsuggested in the literature (goalcongruence, personal interaction,and trust) emerged and are therebyprovided in Table 3d. Many of thevariables that the literaturesuggests tap each construct display

significantly large factor loadingsand each of the constructs appearinternally consistent.

Variation in SC CollaborationEffectiveness Attributed toFirm-Specific Variables

Before conducting an analysis ofthe relationship between theperceived effectiveness of SCcollaboration, the constructs


Table 2dRespondents Profile by Type, Number of Employees, and Annual Sales Revenue

Table 3aFactors Describing Effectiveness


Table 3bTabular Summary of Factor Scores for Measures of Effectiveness

Table 3cFactors Describing Nature of Collaboration

describing the nature of the firm'sSC collaboration, and thecontextual moderators, the effectof a set of firm-specific variablesshown to be important inpredicting SC collaborationeffectiveness was assessed. In thissecond analysis phase, the twoeffectiveness constructs wereregressed against the firm-specificvariables discussed previously andshown in Tables 2c and 2d. Each ofthese five continuous ordinalvariables was represented by aseries of binary dummy variables(the total number of dummyvariables equals the number oflevels in each question minus one).The lowest response level of eachof these variables provides thebasis for determining the statistical

significance of higher levels. Tables4a and 4b provides the higher-level,firm-specific dummy variablesfound by stepwise regression to bestatistically significantly (10%experiment-wise alpha error).

As seen in Table 4a the highest levelof two firm-specific variablesstatistically significantly correlateto enhanced operationalperformance explaining over 10% ofthe total variance of this measure.Companies that collaborate withmore than 75% of their tradingpartners tend to score 3.9 pointshigher on the operationseffectiveness construct andcompanies with over $10 billion insales revenue tend to reportsignificantly greater (3.1 points

higher) operational effectivenessrelated to collaborative SC efforts.Additionally, companies that bothcollaborate extensively and earnover $10 billion in sales per yeartend to have scores that average(11.24 + 3.9 + 3.1 = 18.24) well intothe upper quartile of the operationseffectiveness measure. No level ofthe remaining three firm-specificvariables (number of employees,years in collaboration, and lengthof current agreement) appear tomake a statistically significantimpact on the perceivedoperational effectiveness ofcollaboration.

Turning our attention to theperceived value of collaboration onoverall firm effectiveness, a


Table 3dFactors Describing Contextual Moderators

stepwise regression of firm-specificvariables on this measure wasperformed next (refer to Table 4b).Over 18% of the total variance ofoverall company performance isexplained by four dummy variablesrepresenting three firm-specificvariables: the number ofemployees, the length of thecurrent agreement, and thepercentage partners involved incollaboration. Specifically,companies with longer contractagreement periods (three to fiveyears and ten-plus years) tend toregard more favorably the effect ofcollaboration on overallperformance. Further, the levelrepresenting the longest contractperiod increases the overall

effectiveness score the most (by 5.5points). Interestingly, moderatelysmall companies (201-500employees) on average seem toregard SC collaboration as having arelatively less positive effect onoverall performance. Finally,companies that collaborate withthe greatest percentage (75-100%)of their SC partners tend to rate theeffect of collaboration on overallperformance more highly. Overall, acompany that both collaboratesextensively and enacts agreementperiods of more than ten years, onaverage, scores in the upperquartile on overall effectiveness(17.61 + 5.5 + 2.6 = 25.71).

Variation in CollaborationEffectiveness Attributed toSupply Chain Factors

In this final analysis step, thevariation in operational and overallSC collaboration effectiveness notexplained by firm-specificdifferences (residual variation) wasregressed against the fiveconstructs based on the nature ofcollaboration and the threecontextual moderating constructs.The result of this analysis is shownin Tables 5a and 5b.

Not surprisingly, the variable mostsignificantly related to operationseffectiveness is the extent of


Table 4aStepwise Regression (Response Variables versus Firm-Specific Variables)

Table 4bStepwise Regression (Response Variables versus Firm-Specific Variables)

operations information sharedbetween collaborating firms. Next,firms that extensively share salesand business-planning informationreport statistically significantlyhigher perceived operationaleffectiveness due to collaboration.Finally, firms that report high levelsof congruence between the goals oftheir trading partners andthemselves also report higherlevels of operational effectivenessdue to collaboration.

Likewise, as seen in Table 5b, goalcongruence and extensivelysharing sales and business

planning information each have astrong and positive effect on theperceived overall effectiveness ofSC collaboration. Finally, firms thatextensively use informationsystems collaboratively reporthigher overall effectiveness.

Conclusions and Suggestionsfor Future Research

This research was undertaken tomeasure the impact of factors(nature of collaboration andcontextual moderators) and firm-specific variables on theoperational and overall

effectiveness of SC collaborationusing a refined instrument that wasdeveloped based on the existingliterature. Consistent findings fromour three-step analysis frameworkpoint to a number of conclusions.First, several firm-specific variablesappear to be related to a firm'sperception of the value of SCcollaboration. Larger firms,measured by sales revenue in thecase of operational effectivenessand the number of employees foroverall effectiveness, and firms thatcollaborate extensively tend tovalue the effectiveness ofcollaboration more highly.


Table 5aStepwise Regression (Residuals of Key Firm-Specific Variables versus Main Factors)

Table 5bStepwise Regression (Residuals of Key Firm-Specific Variables versus Main Factors)

Interestingly, we could not confirma link between perceivedeffectiveness and length ofexperience with collaborative SCefforts.

Second, after adjusting forsignificant firm-specific effects, ourresults confirm that extensivelysharing information, joint planning,and using information systemscollaboratively tend to increase theperceived value of collaboration.Finally, goal congruence was theonly contextual modifier that wecould link to SC effectiveness.These results corroborate with theprior research. The nature of SCcollaboration is characterized bythe variables of informationsharing, joint planning, jointproblem solving, joint performancemeasurement, and leveraging (Minet al., 2005). Key dimensions ofcollaboration have been identifiedto include inter-organizationalscope, commitment to workingtogether (joint planning), and acommon vision to achievecollective goals (Sabath et al., 2001;Sheu et al., 2006; Simatupang &Sridharan, 2004; Spekman et al.,2002).

Success of collaboration has beenequated with the ability andreadiness of managers to createtrust and build relationships amongpartners (Panayides & Venus Lun,2009). Trust has been identified asone of the most recognized socialnorms for managing andcoordinating inter-organizationalexchange (Jap, 2001). At anoperational level, the need for openand clear channels for informationsharing has also been recognized(Lejeune & Yakova, 2005; Min et al.,2005; Simatupang & Sridharan,2004). Collaborative efforts usuallyfail when critical long-term detailsare overlooked and strategic plansare not made or followed through(Daugherty et al., 2006). However, itis noteworthy that even thoughpersonal interaction and trust arediscussed repeatedly in theliterature and considered as vital tocollaboration effectiveness, thesefactors were not significant in thisstudy. This was a departure fromprior studies, which suggest thateffective collaboration requires

that partners share a high level oftrust and commitment throughintense personal interaction.

One of the limitations of thisresearch is that it did not look into strategic dimensions ofcollaboration among SC partners.One major area of future research isto study how strategic elementsinteract and play an important rolein assessing the effectiveness of SCcollaboration. Another limitationwas that survey responses wereavailable only from individuals anddid not substantiate perspectivesof other members of the same SC. Amore detailed research that focuseson and includes perspectives of allmembers involved in a partnershipwould prove illustrative.

References

Akintoye, A., McIntosh, G., & Fitzgerald,E. (2000). A survey of supply chaincollaboration and management in theUK construction industry. EuropeanJournal of Purchasing & SupplyManagement, 6, 159-168.

Barratt, M. (2004). Understanding themeaning of collaboration in the supplychain. Supply Chain Management: AnInternational Journal, 9(1), 30-42.

Bensaou, M., & Anderson, E. (1999).Buyer-supplier relations in industrialmarkets: When do buyers risk making idiosyncratic investments?Organization Science, 10(4), 460-481.

Bowersox, D. J., Closs, D. J., Stank, T. P.,& Keller, S. B. (2000). How supply chaincompetency leads to business success.Supply Chain Management Review, 4(4),70-77.

Cassivi, L. (2006). Collaborationplanning in a supply chain. Supply ChainManagement: An International Journal,11(3), 249-258.

Chen, I. J., & Paulraj, A. (2004). Towardsa theory of supply chain management:The constructs and measurements.Journal of Operations Management,22(2), 119-150.

Daugherty, P. J., Richey, R. G., Roath, A.S., Min, S., Chen, H., Arndt, A. D., &Genchev, S. E. (2006). Is collaborationpaying off for firms? Business Horizons,49, 61-70.

Ellram, L. M., & Cooper, M. C. (1990).Supply chain management,partnerships and the shipper-third-party relationship. The InternationalJournal of Logistics Management, 1(2), 1-10.

Evrard-Samuel, K. (2008). Sharingdemand signals: A new challenge toimprove collaboration within supplychains. Supply Chain Forum: AnInternational Journal, 9(2), 16-27.

Flynn, B. B., Schroeder, R. G., &Sakakibara, S. (1994). A framework forquality management research and anassociated measurement instrument.Journal of Operations Management,11(4), 339-575.

Grant, D. B. (2005). The transaction-relationship dichotomy in logistics andsupply chain management. Supply ChainForum: An International Journal, 6(2), 38-48.

Handfield, R. B., & Steininger, W. (2005).An assessment of manufacturingcustomer pain points: Challenges forresearchers. Supply Chain Forum: AnInternational Journal, 6(2), 6-15.

Heikkila, J. (2002). From supply todemand chain management: Efficiencyand customer satisfaction. Journal ofOperations Management, 20(6), 747-767.

Jagdev, H. S., & Thoben, K. D. (2001).Anatomy of enterprise collaboration.Production Planning & Control, 12(5),437-451.

Jap, S. D. (2001). Perspectives on jointcompetitive advantages in buyer-supplier relationships. InternationalJournal of Research in Marketing, 18(2),19-35.

Kwon, I-W. G., & Suh, T. (2005). Trust,commitment and relationships insupply chain management: A pathanalysis. Supply Chain Management: AnInternational Journal, 10(1), 26-33.

Lambert, D. M., & Cooper, M. C. (2000).Issues in supply chain management.Industrial Marketing Management, 29(1),65-83.

Lau, H. C. W., & Lee, W. B. (2000). On aresponsive supply chain informationsystem. International Journal of PhysicalDistribution & Logistics Management,30(7/8), 598-610.


Lee, H. L., & Whang, S. (2000).Information sharing in a supply chain.International Journal of TechnologyManagement, 20(3/4), 373-387.

Lee, P. D. (2005). Measuring supplychain integration: A social networkapproach. Supply Chain Forum: AnInternational Journal, 6(2), 58-67.

Lejeune, M. A., & Yakova, N. (2005). Oncharacterizing the 4 C's in supply chainmanagement. Journal of OperationalManagement, 23, 81-100.

Manthou, V., Vlachopoulou, M., &Folinas, D. (2004). Virtual e-Chain (VeC)model for supply chain collaboration.International Journal of ProductionEconomics, 87, 241-250.

Mason-Jones, R., & Towill, D. R. (1997).Information enrichment: Designing thesupply chain for competitive advantage.Supply Chain Management: AnInternational Journal, 2(4), 137-148.

Matopoulos, A., Vlachopoulou, M.,Manthou, V., & Manos, B. (2007). Aconceptual framework for supply chaincollaboration: Empirical evidence fromthe agri-food industry. Supply ChainManagement: An International Journal,12(3), 177-186.

McClellan, M. (2002). CollaborativeManufacturing: Using real-time plant floorinformation to advance supply chainperformance. Delray Beach, FL: St LuciePress.

Mentzer, J. T., DeWitt, W., Keebler, J. S.,Min, S., Nix, N. W., Smith, C. D., &Zacharia, Z. G. (2001). Defining supplychain management. Journal of BusinessLogistics, 22(2), 1 - 25.

Min, S., Roath, A. S., Daugherty, P. J.,Genchev, S. E., Chen, H., Arndt, A. D., &Richey, R. G. (2005). Supply chaincollaboration: What's happening? TheInternational Journal of LogisticsManagement, 16(2), 237-256.

Myers, M. B., Daugherty, P. J., & Autry, C.W. (2000). The effectiveness ofautomatic inventory replenishment insupply chain operations: Antecedentsand outcomes. Journal of Retailing,76(4), 455-481.

Naesens, K., Pintelon, L., & Taillieu, T.(2007). A framework for implementing

and sustaining trust in horizontalpartnerships. Supply Chain Forum: AnInternational Journal, 7(1), 32-45.

Nakano, M. (2009). Collaborativeforecasting and planning in supplychains: The impact on performance inJapanese manufacturers. InternationalJournal of Physical Distribution &Logistics Management, 39(2), 84-105.

Nunnally, J. C. (1978). Psychometrictheory. New York: McGraw-Hill.

Panayides, P. M., & Venus Lun, Y. H.(2009). The impact of trust oninnovativeness and supply chainperformance. International Journal ofProduction Economics, 122(1), 35-46.

Perrons, R. K. (2005). The long-termirrelevance of trust in outsourcingdecisions for new technologies: Insightsfrom an agent-based model. SupplyChain Forum: An International Journal,6(2), 30-37.

Petersen, K. J., Ragatz, G. L., & Monczka,R. M. (2005). An examination ofcollaborative planning effectivenessand supply chain performance. TheJournal of Supply Chain Management: AGlobal Review of Purchasing and Supply,41(2), 14-32.

Sabath, R. E., Autry, C. W., & Daugherty,P. J. (2001). Automatic replenishmentprograms: The impact of organizationalstructures. Journal of Business Logistics,22(1), 91-105.

Sandberg, E. (2007). Logisticscollaboration in supply chains: Practicevs. theory. The International Journal ofLogistics Management, 18(2), 274-293.

Sheu, C., Yen, H. R., & Chae, B. (2006).Determinants of supplier-retailercollaboration: Evidence from aninternational study. InternationalJournal of Operations & ProductionsManagement, 26(1), 24-49.

Simatupang, T. M, & Sridharan, R.(2004). A benchmarking scheme forsupply chain collaboration.Benchmarking: An International Journal,11(1), 9-30.

Simatupang, T. M, & Sridharan, R.(2005). The collaboration index: Ameasure for supply chain collaboration.International Journal of Physical

Distribution & Logistics Management,35(1), 44-62.

Singh, P. J., & Power, D. (2009). Thenature and effectiveness ofcollaboration between firms, theircustomers and suppliers: A supplychain perspective. Supply ChainManagement: An International Journal,14(3), 189-200.

Skjoett-Larsen, T., Thernoe, C., &Andresen, C. (2003). Supply chaincollaboration: Theoretical perspectivesand empirical evidence. InternationalJournal of Physical Distribution &Logistics Management, 33(6), 531-549.

Soosay, C. A., Hyland, P. W., & Ferrer, M.(2008). Supply chain collaboration:Capacities for continuous innovation.Supply Chain Management: AnInternational Journal, 13(2), 160-169.

Spekman, R. E., Kamauff, J. W., & Myhr,N. (1998). An empirical investigationinto supply chain management: Aperspective on partnerships. SupplyChain Management, 3(2), 53-67.

Spekman, R. E., Spear, J., & Kamauff, J.W. (2002). Supply chain competency:Learning as a key component. SupplyChain Management: An InternationalJournal, 7(1), 41-55.

Stank, T. P., Daugherty, P. J., & Autry, C.W. (1999). Collaborative planning:Supporting automatic replenishmentprograms. Supply Chain Management:An International Journal, 4(2), 75-85.

Stank, T. P., Keller, S. B., & Daugherty, P.J. (2001). Supply chain collaborationand logistical service performance.Journal of Business Logistics, 22(1), 29-48.

Tucci, C., Kaufman, A., Wood, C. H., &Theyel, G. (2005). Collaboration andteaming in the software supply chain.Supply Chain Forum: An InternationalJournal, 6(2), 16-27.

Van Weele, A. J. (2009). Purchasing andsupply chain management (5th Ed.).Stamford, CT: Thompson Learning.

Vickery, S. K., Jayaram, J., Droge, C., &Calantone, R. (2003). The effects of anintegrative supply chain strategy oncustomer service and financialperformance: An analysis of direct



versus indirect relationships. Journal ofOperations Management, 21(5), 523-539.

Vieira, J., Yoshizaki, H., & Ho, L. (2009).Collaboration intensity in the Braziliansupermarket retail chain. Supply ChainManagement: An International Journal,14(1), 11-21.

Vlachos, I. P., & Bourlakis, M. (2006).Supply chain collaboration betweenretailers and manufacturers: Do theytrust each other? Supply Chain Forum:An International Journal, 7(1), 70-81.

Wang, E. T. G., Tai, J. C. F., & Wei, H. L.(2006). A virtual integration theory ofimproved supply chain performance.Journal of Management InformationSystems, 23(2), 41-64.

Zacharia, Z. G., Nix, N. W., & Lusch, R. F.(2009). An analysis of supply chaincollaborations and their effect onperformance outcomes. Journal ofBusiness Logistics, 30(2), 101-123.

About the authors

Amarpreet S. Kohli is an assistant professorat the School of Business, University ofSouthern Maine. He received his Ph.D. inIndustrial Engineering from University ofLouisville, Kentucky. His research interestsinclude supply chain collaboration, leanmanagement, enterprise resource planning,other supply chain management areas usingsimulation, and empirical modelingtechniques. He has published papers invarious peer-reviewed journals and presentedat various national and internationalconferences. He has more than ten years ofexperience in sales and distribution, newproduct development, and quality assurancein various multinational companies.

John B. Jensen is a professor and managingdirector, Center for Global Supply Chain andProcess Management, Moore School ofBusiness, University of South Carolina,Columbia. His research interests include shopfloor design and control, supply chainmanagement, and statistical process control.He consults with public and private sectororganizations on capacity management,benchmarking, resource planning, andtechnology implementation issues. He hasbeen published in Decision Sciences Journal,Decision Sciences Journal of InnovativeEducation, Journal of Operations Management,The International Journal of ProductionResearch, The European Journal ofOperational Research, The Journal of ServicesMarketing, The Credit and FinancialManagement Review, and Maine BusinessIndicators.

assessing effectiveness of supply chain collaboration: …€¦ · sharing information, joint...

Documents