Int. J. Production Economics 136 (2012) 123–130

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Int. J. Production Economics

0925-52

doi:10.1

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197, VIC

E-m

Mesbah

Andy.Ye

Edwin.C

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The relationship between supplier management and firm’s operationalperformance: A multi-dimensional perspective

Daniel Prajogo a,n, Mesbahuddin Chowdhury a, Andy C.L. Yeung b, T.C.E. Cheng b

a Department of Management, Monash University, Australiab Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, PR China

a r t i c l e i n f o

Article history:

Received 22 March 2011

Accepted 27 September 2011Available online 4 October 2011

Keywords:

Supplier management

Long-term relationship

Supplier assessment

Logistics integration

Operations performance

73/$ - see front matter & 2011 Elsevier B.V. A

016/j.ijpe.2011.09.022

espondence to: Department of Management,

3141, Australia. Tel.: þ61 3 9903 2030; fax:

ail addresses: Daniel.Prajogo@monash.edu (D

uddin.Chowdhury@monash.edu (M. Chowdh

ung@inet.polyu.edu.hk (A.C.L. Yeung),

heng@inet.polyu.edu.hk (T.C.E. Cheng).

a b s t r a c t

This paper presents an empirical study on the multidimensional relationships between supplier

management practices and firm operational performance. Specifically, we focus on three supplier

management practices, namely strategic long-term relationship, supplier assessment, and logistics

integration, and test their effects on four operations performance measures, namely quality, delivery,

flexibility, and cost. We use data collected from 232 manufacturing firms in Australia to conduct the

study. Ten hypotheses were tested simultaneously using Structural Equation Modeling (SEM)

technique. The results show that different supplier management practices have different unique effects

on different operations performance measures. Supplier assessment has a positive relationship with

quality performance. Both strategic long-term relationship and logistics integration have positive

relationships with delivery, flexibility, and cost performance. From a theoretical perspective, this study

demonstrates the relative contributions of different kinds of resources (i.e., supplier management

practices in our case) to different performance measures. Our research findings provide practical

insights for managers to understand the effectiveness, as well as the limitations, of different supplier

management practices in enhancing different operations performance measures of firms.

& 2011 Elsevier B.V. All rights reserved.

1. Introduction

The importance of managing suppliers to firms’ operations iswidely acknowledged in the supply chain management (SCM)literature. SCM has been recognized as one of the most importantmanagement functions for achieving long-term competitiveadvantage. As competition intensifies in global markets, firmsface more formidable challenges in improving their performance,from getting quality right to serving disparate and fluctuatingmarkets. As such, many firms have come to realize that it is notsufficient just to focus on improving internal processes—thelesson that they learned in the previous decade through suchconcepts as total quality management (TQM) and lean produc-tion. Competition is now viewed at the supply chain level ratherthan at the individual firm level. At the same time, firms are nowmore focused on their core competence and operations, thusrelinquishing their non-core activities to their supply chainpartners. As a result, acquiring a good understanding of SCM

ll rights reserved.

Monash University, P.O. Box

þ61 3 9903 2718.

. Prajogo),

ury),

practices has become essential to sustaining profitable in today’shighly complex and competitive business world.

SCM requires firms to undertake a set of activities conducive tothe effective management of their supply chains (Li et al., 2006).A number of researchers (Donlon, 1996; Tan et al., 2002; Chenand Paulraj, 2004a; Min and Mentzer, 2004; Kannan and Tan,2006b; Li et al., 2006; Koh et al., 2007; Chow et al., 2008) haveidentified the key activities of SCM. In this study we focus on thesupply chain’s upstream side, which is concerned with suppliermanagement practices. The fact that suppliers play a key role inaffecting firms’ performance has been well recognized in theliterature. One of the possible reasons is the high costs ofpurchased goods and services, which typically account for around70% of the total cost (Ford, 2003). Forging and maintainingcongenial relationships with suppliers has become crucial tofirms to remain competitive in the market. The growing depen-dence of firms on their suppliers has highlighted the need foreffective supplier management (Kannan and Tan, 2002).

Many studies have examined the relationships between SCMpractices, including supplier relationship management, and firmperformance, they commonly show that SCM practices havepositive and significant effects on firm performance at the opera-tions level, as well as at the business level. However, most ofthese studies assume that firms need to implement a broad rangeof SCM practices in order to do well on an array of performance

D. Prajogo et al. / Int. J. Production Economics 136 (2012) 123–130124

measures. Chen and Paulraj (2004a) are pioneers that develop aresearch framework and measures for SCM practices. Their find-ings show that twelve SCM practices (including strategic purchas-ing, long-term relationship, supply base reduction, logisticsintegration, etc.) have significant correlations with supply chainperformance, which spans several dimensions (embracing quality,cost, delivery, flexibility, responsiveness, and customer satisfac-tion). Li et al. (2006) bundle five practices (i.e., strategic supplierrelationship, customer relationship, level of information sharing,quality of information sharing, and postponement) into a holisticmeasure of SCM practices. They show that it has a positiverelationship with a set of performance measures, which includequality, delivery, costs, innovation, and time to market. Taking asimilar approach, Min and Mentzer (2004) combine seven prac-tices (i.e., vision, leadership, long-term relationship, informationsharing, risk and reward sharing, process integration, and coop-eration) to form a bundle of SCM practices and show that it hasa positive relationship with a set of business performancemeasures, which include product offering, availability, timeliness,profitability, and growth.

While the above studies ascertain the competitive value ofSCM practices, they fail to consider three issues. First, it isimportant to consider that not every firm needs or has the abilityor resources to implement a broad range of SCM practices, so it isnot reasonable to consider SCM practices as a ‘‘full package’’.Second, not every firm needs to pursue all the measures ofperformance at the same level simultaneously. Indeed, firmsoften need to focus on one key performance measure over theothers as part of their strategic choice (Corbett and VanWassenhove, 1993). Third, by combining different performancemeasures into one compound measure, these previous studiesassume that SCM practices have positive effects on differentperformance measures at more or less equal levels. This assump-tion is questionable as the literature has shown that differentperformance measures have different characteristics, so differentresources are required to achieve them. This is the area where thepast studies on SCM have yet to address by investigating theunique effects of different SCM practices on different performancemeasures. Compounding different SCM practices and differentperformance measures does not help firms to identify the indivi-dual contribution of an SCM practice to a specific type ofperformance. We aim to fill this research gap by demonstratingthe unique effects of different SCM practices on different opera-tions performance measures. Specifically, we focus on examiningthe relationships between three supplier management practices

(i.e., strategic long-term relationship, supplier assessment, andlogistics integration) and four operations performance measures

(i.e., quality, delivery, flexibility, and cost).This study contributes to the literature in two ways. First, from

a theoretical perspective, different performance measures requiredifferent configurations of resources. In this regard, we demon-strate the relative effects of different kinds of resources (i.e.,different supplier management practices in our case) on differentoperations performance measures. As mentioned earlier, not allSCM practices are considered important, so it is necessary tounderstand the effectiveness of each supplier management prac-tice in helping firms to pursue their different strategic goals inoperations. Second, from a practical perspective, it is importantfor managers to understand the fit between resources andperformance. Failing to do so will result in poor firm performancedue to either a lack of effective resources or investment inredundant resources that do not match firms’ competitive stra-tegies, thus undermining the efficiency of their operations. Thisstudy, therefore, provides insights for managers in selecting thespecific resources they need to achieve the strategic goals of theirfirms’ operations.

2. Literature review and hypotheses

In this study we focus on examining the effects of threesupplier management practices, namely strategic long-term rela-tionship, supplier assessment, and logistics integration, on firms’operations performance. We acknowledge that we do not addresssupplier management practices in the most comprehensive way.Nevertheless, we consider that the three selected supplier man-agement practices are key elements of SCM that have been widelyrecognized in the SCM literature (e.g. Tan et al., 2002; Chen andPaulraj, 2004b; Li et al., 2005). In addition, three major points leadus to focus on these three supplier management practices asoutlined below.

First, it is our understanding that these three supplier manage-ment practices capture two important aspects of SCM, namelyselecting the right supplier (who) and building the right relation-ship (how). The ‘‘who’’ aspect is represented by supplier assess-ment, and the ‘‘how’’ aspect is represented by strategic long-termrelationship (a social construct) and logistics integration(a technical construct). Second, these three practices reflect theevolution of supplier management over the past three decades,beginning with supplier assessment, followed by long-termrelationship, which was very popular during the TQC/TQM era.Long-term relationship with supplier has since been expandedinto integration with supplier in the past decade, primarily withthe emergence of Information and Communications Technology(ICT). Third, our literature review suggests that these threepractices represent the key aspects of SCM practices. Over thepast decade, the importance of buyers developing long-termrelationships between with their suppliers has been well docu-mented in the SCM literature. In order to strengthen the relation-ships, buyers need to continuously monitor their supplierperformance across multiple dimensions and provide feedbackfor improvement (La Londe and Cooper, 1989; Talluri and Sarkis,2002). In addition, firms now expect their suppliers to attain andmaintain established standards of product quality, service,distribution, promotion, and partnering (Lai et al., 2005). Withoutcarefully monitoring supplier performance, firms will be unableto assess whether their key suppliers can meet the currentdemand and will be able to continue business in the future. Thatis why supplier assessment and monitoring has been consideredas a key aspect of SCM that helps buyer firms sustain long-termrelationships with supplier firms. As SCM is an integrative func-tion (Freeman and Cavinato, 1990; Ellram and Krause, 1994;Hakansson and Gadde, 1994), integration could occur with othersfirms along the supply chain (upstream and downstream) interms of material and information (Perona and Saccani, 2004).

The above three points justify our decision to include in ourframework logistics integration that embraces the integration ofinformation and materials along the supply chain as a suppliermanagement practice. The next section will elaborate on thespecific relationships between the three supplier managementpractices and the four dimensions of operational performance.

2.1. Long-term relationship with supplier

Strategic long-term relationship with supplier can be definedas long-term relationships between a firm and its suppliers(Li et al., 2006). It plays an important role in enabling the firmto respond to dynamic and unpredictable changes occurring inthe business environment (Hoyt and Huq, 2000). It focuses oninitiatives that enhance superior relational characteristicsbetween supply chain members and create a win–win situationfor the buyer and its suppliers instead of adversarial relationships(Paulraj and Chen, 2005). Through close relationships withsuppliers, buyers are more willing to share risk and reward,

D. Prajogo et al. / Int. J. Production Economics 136 (2012) 123–130 125

encourage mutual planning and problem-solving efforts, andmaintain the relationships over a longer period of time (Cooperand Ellram, 1993; Stuart, 1993; Chen et al., 2004; Li et al., 2007).

In the context of supply chain management, effective supplierrelationships are an important element of a cutting-edge supplychain, which have a lasting effect on the competitiveness of theentire supply chain (Choi and Hartley, 1996; Kotabe et al., 2003).Specifically, forging long-term relationships with key suppliers ina competitive business environment helps firms achieve superiorperformance by reducing cost, improving quality, and enhancingcustomer responsiveness or flexibility (De Toni et al., 1994).Strategically, strategic supplier management includes activitiesthat represent an investment in transaction specific assets thatmay yield the benefits of vertical integration (e.g., lower costs,better communication, coordination, and quality) without incur-ring the costs of actual ownership (Carr and Pearson, 1999). Thisis because strategic relationship under the conditions of a‘‘regular’’ long-term contract with suppliers involves more thanjust transactional activities (i.e., selling–buying), but also high-level coordination of suppliers’ systems and capabilities, whichhas positive effects on cost, quality, and cycle time (Monczkaet al., 1998). The above discussion suggests that strategic long-term relationships with suppliers bring potential benefits thatspan the four major operational aspects, namely quality, delivery,cost, and flexibility. Accordingly, we hypothesize that

Hypothesis 1a. Strategic long-term relationship with supplier is

positively related to firm’s quality performance.

Hypothesis 1b. Strategic long-term relationship with supplier is

positively related to firm’s delivery performance.

Hypothesis 1c. Strategic long-term relationship with supplier is

positively related to firm’s flexibility performance.

Hypothesis 1d. Strategic long-term relationship with supplier is

positively related to firm’s cost performance.

2.2. Supplier assessment

Supplier assessment is defined as the assessment of suppliercapability and performance as compared with other similarcompanies for the purpose of providing the necessary input tothe buyer firm in the long run and to improve the buyer firm’sperformance (Talluri and Sarkis, 2002). In this definition supplierperformance means a supplier’s demonstrated ability to meet thebuyer’s requirements and supplier capability refers to a supplier’spotential that can be leveraged to the buyer’s advantage in thelong run (Sarkar and Mohapatra, 2006). In today’s businessenvironment where competition has shifted from firm level tosupply chain level, suppliers play a key role in affecting theoverall performance of the supply chain. In this regard, monitor-ing supplier performance and capability is critically important tothe buyer firm (Huang and Keskar, 2007). An important part ofthis assessment process is to provide evaluation feedback tosuppliers since this feedback clarifies the buyer’s expectationand direct suppliers for further improvement (Krause et al.,2000). Monczka et al. (1993) point out that evaluating supplierperformance is necessary to develop critical product and processcategories with key suppliers. Peterson et al. (2005) also stressthe importance of detailed supplier assessment for integratingsuppliers into new product development. In addition, firms arealso keen to seek suppliers who are capable in engineering,design, testing, manufacturing, tooling, delivery, and responsive-ness (Narasimhan et al., 2001). Therefore it becomes a criticalresponsibility of purchasing managers to monitor and evaluatesupplier performance and capability with respect to their

strategic needs (Hahn et al., 1990; Narasimhan et al., 2001;Talluri and Sarkis, 2002).

Several studies (Giunipero, 1990; Billesbach et al., 1991; VanDer Rhee et al., 2009) have empirically examined the criteria forsupplier assessment and suggest that, other than cost, quality,delivery, and service are the most important assessment criteria.Krause et al. (2000) show that supplier assessment strategy has adirect and positive impact on performance improvement of thebuyer firm. Specifically, supplier assessment is important inensuring that a supplier has demonstrated the ability to meet abuyer’s requirements in terms of cost, quality, delivery, or service(Sarkar and Mohapatra, 2006). Consequently, studies have showna positive correlation between the assessment of a supplier’sdelivery and quality performance and the buying firm’s productquality and competitive position (Kannan and Tan, 2002). Ingeneral, the literature suggests that supplier assessment haspositive effects on three major dimensions of operational perfor-mance, namely quality, delivery, and cost. Accordingly, wehypothesize that

Hypothesis 2a. Supplier assessment is positively related to firm’s

quality performance.

Hypothesis 2b. Supplier assessment is positively related to firm’s

delivery performance.

Hypothesis 2c. Supplier assessment is positively related to firm’s

cost performance.

2.3. Logistics integration

Logistics integration is a relatively new notion, which reflectstransformation of manufacturing enterprises to encompass theentire supply chain, not an individual company, as a competitiveunit (Greis and Kasarda, 1997). Increasing competition has drivenfirms to not only improve their internal operations (such asprocess control and inventory management), but also focus onintegrating their suppliers into the overall value chain process(Yeung et al., 2009). The essence of logistics integration is well-coordinated flow of materials from suppliers, which allow firmsto have a smooth (seamless) production process (Frohlich andWestbrook, 2001). Higher levels of integration are characterizedby increased logistics-related communication, greater coordina-tion of the firm’s logistics activities with those of its suppliers andcustomers, and more blurred organizational distinctions betweenthe firm’s logistics activities and those of its suppliers andcustomers (Stock et al., 1998; Stock et al., 2000). Such coordina-tion produces seamless connections between firms and suppliersin such a way that the boundaries of the activities between thetwo parties are blurred. As a result, logistics integration allowscompanies and their suppliers to act as a single entity, whichwould result in improved performance throughout the chain(Tan et al., 2002).

Past research has suggested that logistics integration deliversoperational benefits (Van Der Vaart and Van Donk, 2008).Successful integrated logistics management ties all the logisticsactivities together in a system that simultaneously works tominimize the total distribution cost and attain the desiredcustomer level (Daugherty et al., 1996). Indeed, logistics supporthas been recognized as a critical element in just-in-time andother time-based competitive strategies (Mcgrath and Hoole,1992; Fawcett et al., 1997). This focus clearly reflects theimportance of logistics as a source of customer value andcompetitive advantage (Vonderembse et al., 1995; Stock et al.,2000). Previous empirical evidence suggests a positive linkbetween logistics integration and increased efficiency and pro-ductivity (Larson, 1994; Frohlich and Westbrook, 2001; Kim,

D. Prajogo et al. / Int. J. Production Economics 136 (2012) 123–130126

2009). Logistics integration provides firms with a way to improveperformance on multiple competitive dimensions, most particu-larly cost, flexibility, and delivery performance (Stock et al., 1998).Using a stochastic cost model, Wei and Krajewski (2000) showthat cost penalties are reduced substantially if firms adopt aparticular level of supply chain integration. In the context ofinternational operations, logistics integration plays an even moreimportant role where firms need to coordinate geographicallydispersed global operations, especially when they pursue time-based strategies (Fawcett et al., 1997). The above arguments andstudies suggest that logistics integration has a positive effect onoperational performance in terms of delivery, flexibility (orresponsiveness), and cost (or efficiency). Accordingly, wehypothesize that

Hypothesis 3a. Logistics integration is positively related to firm’s

delivery performance.

Hypothesis 3b. Logistics integration is positively related to firm’s

flexibility performance.

Hypothesis 3c. Logistics integration is positively related to firm’s

cost performance.

3. Method

3.1. Sample and procedures

We collected the data for this study from managers ofAustralian manufacturing firms via mail survey between end of2008 and early 2009. We randomly selected the respondents froma list of manufacturing firms purchased from a mailing listcompany. We mailed out a total of 1800 survey questionnairesand received 232 usable responses, attaining a 13.1% responserate. We checked the data for bias using correlations of responsesbetween early respondents and late respondents based on indus-try sector and organizational size. The chi-square tests on bothcategories did not indicate any significant differences betweenthe two groups of respondents.

The dataset used in this study has been used in two otherstudies (Prajogo and Olhager, 2011; Olhager and Prajogo, 2012).Olhager and Prajogo (2012) analyze differences between twoproduction systems (Make-To-Stock versus Make-To-Order) withregard to the role that supply chain management practices play inenhancing business performance. Prajogo and Olhager (2011)examine the integration of information (technical and socialdimensions) and the integration of material (logistics) betweenfocal firms and their suppliers. While each paper includes logisticsintegration as a key variable, it considers logistics integration in adifferent research framework and incorporates a different set ofvariables of interest according to the specific purpose of the study.

In terms of industry sector, 16% of the respondents came fromelectronic/electrical, 25% from machinery, 8% from automotive,11% from chemical, 4% from food processing, 7% from construc-tion, and 12% from other manufacturing sectors. The remainingsectors identified as ‘‘others’’ included medical equipment, wood,printing and paper, and defense. In terms of organizational size(based on number of employees), 46% of the respondents camefrom firms with fewer than 100 employees, 35% of the firms havebetween 100 and 500 employees, and the remainder 19% of therespondents came from large manufacturing firms with over 500employees. Nearly half of the respondents (45%) held a position asoperations managers, 27% supply chain/logistics managers, 18%procurement/purchasing, and 3% customer services managers.

3.2. Non-response bias

Non-response bias was tested in two ways. First, randomfollow-up phone calls were made to identify the firms thatdeclined to participate in the survey. Reasons for non-participa-tion stated by non-respondent companies (30 such companieswere identified in this process) included lack of time, lack ofresources, and not interested. None of these reasons alluded tothe possibility that there were systematic reasons for not parti-cipating in the study. Second, the correlation of responsesbetween early respondents and late respondents in this studywere analyzed (Armstrong and Overton, 1977; Lambert andHarrington, 1990). The chi-square test did not indicate anysignificant difference between early and late responses. Theseresults suggest that non-response bias was not a substantiveproblem in this data set.

3.3. Measures

To measure strategic long-term relationship and logisticsintegration, we adopt the scales of Chen and Paulraj (2004a).For supplier assessment, we adapt items from previous empiricalstudies, including Kannan and Tan (2006a) and Krause et al.(2000). We use a Likert-scale ranging from 1 (strongly disagree)to 7 (strongly agree) to measure the degree of implementation ofthe three supplier management practices. In responding to thissection, we asked the respondents to focus on the key supplierswith whom the firms conduct maximum business value indollar terms.

We adapt from the scales of Naor et al. (2008) to evaluate thefour operations performance (quality, delivery, flexibility, andcost) measures. We invited the respondent to assess their firm’soperations performance relative to the best competitor in themarket with the scale ranging from 1 (weakest in the industry) to7 (strongest in the industry). Table 1 presents all the items used inthis study.

4. Results

4.1. Scale validity and reliability

We performed a confirmatory factor analysis (CFA) to simul-taneously validate the measures for all the variables (constructs)considered in this study. Table 1 presents the results of theconfirmatory factor analysis and the Cronbach’s alphas. Allthe items loaded significantly on their corresponding constructs.The item loadings and the overall model fit results suggest acceptableunidimensionality and convergent validity of the measures as theloading paths were above 0.5 (Carmines and Mciver, 1981; Bollen,1989; Bagozzi et al., 1991; Hoskisson et al., 1993).

The Cronbach’s alphas suggest satisfactory reliability of thethree supplier management constructs (Nunnally, 1978). Sincethe four operational performance scales only comprise two items,we used the Pearson r correlation between the two items withinthe scale (instead of Cronbach’s alpha) to assess the reliability. Allthe correlations were significant at po0.01 and the Pearson r

coefficients fell within or above the optimal range between0.2 and 0.4 for inter-item correlation suggested by Briggs andCheek (1986).

4.2. Common method variance

We used Harman’s single-factor test to check for commonmethod variance (Podsakoff and Organ, 1986). We conducted thetest using the principal component analysis and loading all 21

ap < 0.1 * p < 0.05, ** p < 0.01

χ2 = 439.09 df = 204 RMSEA = 0.07 NFI = 0.91 CFI = 0.95 GFI = 0.86

SupplierAssessment

LogisticsIntegration

Strategic Long-term Relationship

Quality

Delivery

Flexibility

Cost0.18*

0.26**

0.19*

0.22**

0.02

0.25**0.17*

0.15a

0.21**

0.01

Fig. 1. Path diagram of structural equation modeling.

Table 1Scale validity and reliability for supplier management practices and performance.

Scale Item Loading Cronbach’salpha

Strategic long-term

relationship

We expect our relationships with key suppliers to last a long time 0.71 0.88

We collaborate with key suppliers to improve their quality in the long run 0.80

The suppliers see our relationships as a long-term alliance 0.87

We view our suppliers as an extension of our company 0.85

Logistics integration Inter-organizational logistic activities are closely coordinated 0.72 0.90

Our logistics activities are well integrated with suppliers’ logistics activities 0.83

We have a seamless integration of logistics activities with our key suppliers 0.90

Our logistics integration is characterized by excellent distribution, transportation and/or warehousing

facilities

0.87

The inbound and outbound distribution of goods with our suppliers is well integrated 0.72

Supplier assessment We have a formal supplier assessment system to determine their capabilities 0.81 0.90

We set a clear metric for measuring performance of our suppliers 0.89

We monitor closely the performance of our suppliers 0.87

We compare our supplier performance with other similar companies 0.70

Quality Conformance to specification 0.87 0.70a

Product quality performance 0.85

Delivery On-time delivery 0.82 0.71a

Speed of delivery 0.93

Flexibility Volume or capacity flexibility 0.58 0.37a

Degree of product variety 0.66

Cost Overall operations costs 0.74 0.59a

Competitive prices of our products 0.85

w2¼232.64, df¼168, RMSEA¼0.06, NFI¼0.93, CFI¼0.97, GFI¼0.88

a Since the scale only comprises two items, Pearson r correlation, instead of Cronbach’s alpha, is used to assess reliability. The correlation is significant at po0.01.

D. Prajogo et al. / Int. J. Production Economics 136 (2012) 123–130 127

items onto one common factor. The test checks if one single factorwould emerge from factor analysis, which would point towardsthe presence of common method bias. The procedure involvedtesting a one-factor measurement model where all 21 items wereloaded onto a single latent construct. The results of this test showthat the one-factor model produced was a poor fit with the data(w2¼1933.20; df¼188; RMSEA¼0.20; NFI¼0.67; CFI¼0.69;

GFI¼0.55) and many of the items suffered from poor pathloadings (o0.3). We therefore conclude that common methodsbias was unlikely to be present in our data set.

4.3. Discriminant validity

As an additional check, we conducted a discriminant validityanalysis to examine if the explanatory and dependent constructssignificantly overlap one another. Following Venkatraman (1989),we established discriminant validity by conducting a CFA on eachpair of the constructs in this study. For each pair, we performedthe CFA twice. In the first CFA, we allowed the two constructs tobe freely correlated and estimated the chi-square value of themodel. In the second CFA, we fixed the correlation betweenthe two constructs at 1.0 and estimated the chi-square value ofthe model. If the difference between the chi-squares obtainedfrom the first and the second CFA (i.e., Dw2) is greater than thechi-square value at the degree of freedom of 1 and significancelevel of po0.01 (i.e., 6.64), there is reasonable evidence ofdiscriminant validity of the constructs (Ahire et al., 1996). Withseven constructs incorporated in this study, we conducted 21chi-square tests. The Dw2 values for all the tests confirm dis-criminant validity of the constructs and provide further evidenceon the absence of common method variance.

4.4. Structural relationships

We present the results of the structural equation model (SEM)in Fig. 1. Overall, the model showed a good fit with all the fit

indices (NFI¼0.91; CFI¼0.95; GFI¼0.87; RMSEA¼0.07) deemedacceptable. We included organizational size (in terms of numberof employees) and process type (ranging from (1) assembly line to(5) project) as control variables and found no significant effect onany of the operations performance measure, except for onenegative path between process type and delivery performance.

The findings support seven of the ten hypotheses posed in thisstudy. Strategic long-term relationship has a positive effect on allthe performance measures, except quality, thus Hypotheses1b–1d were supported, but Hypothesis 1a was rejected. Supplierassessment has a positive relationship with quality, supportingHypothesis 2a, but not with delivery and cost, rejectingHypotheses 2b and 2c. Logistics integration has a positive rela-tionship with delivery, flexibility, and cost, so Hypotheses 3a–3cwere supported. Table 2 summarizes the results of the hypothesistesting.

Table 2Summary of the results of hypothesis testing.

Hypotheses Results

Hypothesis 1a: Strategic long-term relationship with supplier is positively related to firm’s quality performance. Rejected

Hypothesis1b: Strategic long-term relationship with supplier is positively related to firm’s delivery performance. Supported

Hypothesis 1c: Strategic long-term relationship with supplier is positively related to firm’s flexibility performance. Supported

Hypothesis 1d: Strategic long-term relationship with supplier is positively related to firm’s cost performance. Supported

Hypothesis 2a: Supplier assessment is positively related to firm’s quality performance. Supported

Hypothesis 2b: Supplier assessment is positively related to firm’s delivery performance. Rejected

Hypothesis 2c: Supplier assessment is positively related to firm’s cost performance. Rejected

Hypothesis 3a: Logistics integration is positively related to firm’s delivery performance. Supported

Hypothesis 3b: Logistics integration is positively related to firm’s flexibility performance. Supported

Hypothesis 3c: Logistics integration is positively related to firm’s cost performance. Supported

D. Prajogo et al. / Int. J. Production Economics 136 (2012) 123–130128

For confirmatory purposes, we ran a competing model toexamine if the tested model is the best model by adding twoadditional paths that were not estimated in the tested model (i.e.,assessment-flexibility and integration-quality). The competingmodel did not show any improvement in fit and did not produce asignificant reduction in chi-square value. Neither of the twoadditional paths was found to be statistically significant. Thisresult confirms the validity of the tested model.

5. Discussion of the findings

The findings provide a number of insights on the relationshipsbetween supplier management practices and firm performance.First, the findings reveal different supplier management practicesdiffer in their effectiveness in enhancing different dimensions ofoperational performance. In particular, this study demonstratesthe uniqueness of supplier assessment and logistics integrationwith the former showing a positive relationship only with quality,while the latter showing a positive relationship with delivery,flexibility, and cost. Strategic long-term relationship shows apositive relationship with all the operations performance mea-sures, except quality.

The non-supported hypotheses, although somewhat surpris-ing, provide important lessons. Supplier assessment does notshow a significant relationship with delivery and cost. From thecost perspective, this result is somewhat unexpected becausesupplier assessment aims to prevent poor quality of incomingmaterials, which would minimize the cost of defects. However,this result could be understood from the perspective that cost isnot the major criterion for selecting suppliers, particularly fornon-commodity (specialty) components or materials. The non-significant relationship between supplier assessment and deliveryis also surprising given that dependability is normally included inthe criteria for selecting suppliers. However, this finding suggeststhat while choosing the right suppliers is important, it is notsufficient to achieve high performance in delivery and costefficiency. As the results show, good performance in deliveryand cost requires partnership and integration with suppliers.

The non-significant relationship between strategic long-termrelationship and quality is unexpected. On scrutinizing the result,we see that the result is in the right direction as the pathcoefficient was positive and significant at po0.1. This findingsuggests that in order to ensure high quality materials orcomponents, strict supplier assessment and continuous monitor-ing of suppliers’ performance is the key factor, rather than simplybuilding relationships with suppliers. For example, firms requiretheir suppliers to be certified to ISO 9001 or they conduct qualityaudits of their suppliers. However, the finding suggests thatsupplier assessment needs to be conducted in the context ofbuilding strategic long-term relationships with suppliers, instead

of being taken as a once-off transaction (or arm’s lengthrelationship).

Logistics integration, on the other hand, shows a positive effecton delivery, flexibility, and cost. First, as suggested in theliterature, logistics integration reflects a broader view of opera-tions from intra-firm level to inter-firm level, where well-coordi-nated flows of materials from suppliers allow firms to runseamless production processes. Such coordination allows compa-nies and their suppliers to operate as a single entity, which wouldresult in the potential benefits of vertical integration (quality,dependability, planning and control, and lower costs) withouthaving it in the physical sense. Logistics integration is also anessential requisite for improving swiftness and even flow in theproduction system, which has a positive effect on delivery time(speed), flexibility, and cost.

Second, the results provide insights on the key aspects inmanaging supply chains, particularly on the upstream side. In thisregard, the results suggest that building overall good relation-ships and integration with suppliers are no less important thanchoosing the right suppliers. Indeed, our findings show thatchoosing the right suppliers only affects quality while jointlyestablishing relationships and integration with suppliers havesignificant effects on delivery, flexibility, and cost. The non-significant effect of supplier assessment on delivery, flexibility,and cost provides an important message that firms will not beable to capitalize on the capability of their (chosen) suppliersunless they are able to develop strategic long-term relationshipand building logistics integration with them.

Third, this study identifies the key supplier managementpractices that contribute to the improvement of firms’ operationsperformance. As different supplier management practices lead todifferent performance outcomes, firms need to focus on specificsupplier management practices that reflect the best configurationto achieve their targeted performance. This means that firms donot necessarily need to implement a broad range of suppliermanagement practices in their operations, rather, they needto understand first their operations’ objectives and select thespecific supplier management practices that best enable them toattain their desired performance outcomes.

Finally, from a broader perspective, the unique effects of thethree supplier management practices demonstrate the need forintegrating two major concepts of operations, namely TQM andjust-in-time (JIT), from the supply chain perspective. TQM empha-sizes supplier assessment and strategic long-term relationship(Willborn and Cheng 1994), while JIT is focused on logisticsintegration to improve incoming scheduling and minimize inven-tory (Cheng and Podolsky, 1996). This link is further confirmedwith the positive correlation between the three supplier manage-ment practices, suggesting the need for implementing the threepractices simultaneously to achieve multiple dimensions ofperformance as sources of competitive advantage. This study

D. Prajogo et al. / Int. J. Production Economics 136 (2012) 123–130 129

therefore corroborates the literature that suggests that TQM andJIT should be employed in tandem in order to maximize theirimpacts on enhancing broader dimensions of operational perfor-mance (Flynn et al., 1995; Withers et al., 1997; Vokurka et al.,2007). Furthermore, the findings show that strategic long-termrelationship can be considered as an overarching supplier man-agement practice as it has a positive relationship with four majoroperations performance measures. This indicates that this prac-tice is required regardless of the kind of performance underpursuit. In other words, it lays the foundation for other suppliermanagement practices, which have more specific effects oncertain operations performance measures.

From a theoretical perspective, our results provide support forboth resource-based view (RBV) and relational view (RV) theories.RBV suggests firms are successful because they own specificresources that are heterogeneous across firms (Wernerfelt,1984). Furthermore, RBV argues that such resources should bevaluable, immobile, and inimitable before they can producecompetitive advantage (Barney, 1991). In this regard, suppliershave been considered as an integral asset of a firm’s operationsapart from the firm’s internal processes. In recent years, firmshave increased their level of outsourcing in the face of increasingcompetition as they are focusing on their core competence. Theincreased outsourcing has increased dependence on suppliers;hence, changing the paradigm of considering suppliers as simplytrading partners into resources. Consequently, firms must bemore careful in selecting their suppliers in the expectation thatthey would be able to develop these suppliers’ capabilities to bepart of their competitive resources through building long-termrelationship and integration (Krause et al., 2000; Lai et al., 2005).At the same time, according to relational view theory (Dyer andSingh, 1998), firms build their competitive advantage in anexchange relationship with their partners in order to gain accessto and exploit the complementary resources owned by theirpartners. Such relationships are necessary because firms do nothave the specific capabilities that their partners have (becausesuch capabilities are difficult to imitate). The inter-firm relation-ships (collaboration, cooperation, or integration) allow firms toaccess competitive resources and overcome their internal defi-ciencies (Ahuja, 2000). In the context of supply chains, relationalview theory explains why firms collaborate with their suppliersas they may not have the requisite resources and capabilities tomake the components or materials that are produced by thesesuppliers.

6. Conclusion and limitations

As with any study, our research is subject to a number oflimitations. We address these issues and offer recommendationsfor future research on them. As mentioned earlier, this study doesnot comprehensively capture all SCM practices, rather it seeks todemonstrate the unique effects of different supplier managementpractices on operations performance measures. Consequently,future studies can perform similar tests with other practices thatare no less important than those tested in this study, such assupplier involvement and information sharing. Also, we limit ouranalysis to the combinatorial or additive effects of differentsupplier management practices. Future studies can test theinteractive effects between different supplier management prac-tices to investigate the synergistic or antagonistic effects amongthem in predicting various measures of operations performance.From a methodological perspective, while we believe that the useof 2-item scales is permissible, we recommend the use of morethan two items in the scale in future studies to improve thereliability and robustness of the scales.

In terms of generalizability of the findings, this study capturescross-sectoral manufacturing data and therefore has both advan-tages and disadvantages. On the positive side, the findings couldrepresent what happens in most manufacturing sectors. On thedownside, the findings suffer from the limitation of addressingindustry-specific issues that could affect the tested relationships.We have sought to minimize this problem by controlling theperformance by firm size and process type. As such, we recom-mend that future studies seek to perform comparative analysesbetween sectors with different characteristics (e.g., mass produc-tion versus customization) and test if specific SCM practices canbe employed for achieving different outcomes in different indus-try sectors. In conjunction with the above point, this study isfocused on Australian manufacturing firms, which could beconsidered as representing developed countries. The level ofknowledge on SCM practices among Australian managers couldbe considered as relatively advanced that they can capitalize onthe benefits of building supply chain networks with their supplychain partners as reflected in the findings. The question iswhether these findings would be as applicable in other lessdeveloped countries where firms are still primarily focused oninternal capabilities and lack of international exposures in build-ing their competitive advantage.

Finally, by testing the direct effects of SCM practices onperformance, our study considers the firm’s internal operationsas a ‘‘black box’’. While internal operations management is notpart of our study, future research can extend our findings bytesting the mediating variables (inside the manufacturing firm),which helps unravel the value chain links from inbound tooutbound performance.

Acknowledgments

We thank the anonymous referees for their many helpfulcomments on earlier versions of our paper. A.C.L. Yeung andT.C.E. Cheng were supported in part by the Research GrantsCouncil of Hong Kong under grant number PolyU 5518/10H.

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