The current issue and full text archive of this journal is available at www.emeraldinsight.com/1463-5771.htmBIJ18,6 Supply chain management practices in the electronics industry in Malaysia834 Consequences for supply chain performance Veera Pandiyan Kaliani Sundram Department of Business, Universiti Teknologi MARA, Segamat, Malaysia Abdul Razak Ibrahim Department of Business, University Malaya, Kuala Lumpur, Malaysia, and V.G.R. Chandran Govindaraju Malaysian Industry-Government Group for High Technology, Selangor, Malaysia Abstract Purpose – The purpose of this paper is to explore the effects of different dimensions of supply chain management practices (SCMP) on supply chain performance (SCP) in the electronics industry in Malaysia. Design/methodology/approach – The study employed the quantitative method where convenience sampling and self-administrated survey questionnaires were sent to 125 electronics ﬁrms in Malaysia. The research framework was tested using variance-based structural equation model, the partial least squares (PLS) method. Findings – The empirical results of PLS indicate that six of the seven dimensions of SCMP have a signiﬁcant positive effect on SCP. Furthermore, agreed vision and goals shows a greater inﬂuence than other dimensions of SCMP. Research limitations/implications – This study took a narrow focus solely on the electronics manufacturing industry with a relatively small sample size of respondents. Also the data were only collected from single respondents in an organization. However, being the ﬁrst study to explore the dimensions of SCMP and how those dimensions relate to SCP, the study shapes the pathway for future research. Practical implications – The results offer insights to SCM practitioners and policy makers on the importance of SCMP to increase the competitiveness of manufacturing industry in terms of SCP. Originality/value – This study employs a newly developed framework based on existing theoretical arguments to empirically examine the relationship between two important factors, the SCMP and SCP. This study is perhaps one of the ﬁrst to address the effect of SCMP that includes combination of comprehensive practices and system approach towards the overall performance of the supply chain. Keywords Supply chain management practices, Performance, Manufacturing industries, Partial least squares, Malaysia, Electronics industry Paper type Research paper The authors are grateful to James Kunaratnam for his comments and editorial work. They also thank IAMOT conference participants, the anonymous referees and the Editor of this journal forBenchmarking: An International their valuable comments.JournalVol. 18 No. 6, 2011 This article is part of the special issue: “Supply chain networks in emerging markets” guestpp. 834-855 edited by Harri Lorentz, Yongjiang Shi, Olli-Pekka Hilmola and Jagjit Singh Srai. Due to anq Emerald Group Publishing Limited1463-5771 administrative error at Emerald, the Editorial to accompany this special issue is publishedDOI 10.1108/14635771111180725 separately in BIJ Volume 19, Issue 1, 2012.
1. Introduction Supply chainGlobalization has driven many corporations to widen their resources and capability managementenhancement from internal environmental practices to greater heights. Attention isincreasingly shifting towards external collaboration and networking outside the practicesboundaries of the organization. This requirement has became essential in order to becompetitive locally and across the borders (Oliver and Webber, 1982; Lambert et al.,1998). As to achieving this, organizations need to have strong upstream and 835downstream integration of their elaborate network of business relationships. Therefore,there is an imminent need for supply chain management (SCM) in all sectors across eachvalue chain entities. SCM has drawn increasing attention from many practitioners andscholars in recent years (Bechtel and Jayaram, 1997; Burgess et al., 2006) due to thebeneﬁts of SCM for operational success (Croom et al., 2000). In the corporate world, inorder to meet customer requirement, the integration of various business processes suchas demand planning and forecasting, procurement, manufacturing and assembly,distribution and return of effective and efﬁcient management of ﬂow of resources frompoint of origin to point of destination has become important parts of SCM (Lummus andVokurka, 1999; Mentzer et al., 2001; New, 1997). SCM also includes the total connectivitybetween the upstream (supply and manufacturing) and downstream (distribution) valuechain entities in order to achieve competitiveness (Hong and Jeong, 2006; Boddy et al.,2000). Similarly, Hong and Jeong (2006) referring to the works of Carmignani (2009),Lambert and Cooper (2000) and Zhao and Simchi-Levi (2002), deﬁned SCM as: [. . .] is a set of approaches utilized to effectively integrate suppliers, manufacturers, logistics, and customers for improving the long-term performance of the individual companies and the supply chain as a whole.As such, the primary role of SCM is to meet customer requirement in terms of providingcustomer with the right product (Dale et al., 1994) of right quality (Carmignani, 2009;Brewer and Speh, 2000) and quantity (Chan et al., 2001) from a right source (Carr andSmeltzer, 1999) at right price (Chin et al., 2004), and ﬁnally the utilizing the righttechnology (Boubekri, 2001; Basnet et al., 2003). The strategic nature of SCM practices(SCMP) will be able to explain the dual purpose of SCM namely to improve theperformance of an individual organization and to improve the performance of the entiresupply chain (Wong et al., 1999). In order to be highly competitive and to achievesustainable proﬁtability growth, SCM seeks close integration of internal functionswithin ﬁrm and external linking with suppliers, customers, and other channel members.This could be achieved through effective construction of various SCMP (Kim, 2006).Literatures have highlighted on the need to understand SCMP, which is becoming anessential prerequisite, to staying in the competitive global race and to grow proﬁtably(Power et al., 2001; Moberg et al., 2002; Sezen, 2008). However, in spite of the key role of SCMP, far limited and scant scholarly investigationhas been undertaken to present a theoretical viewpoint, supported by empirical evidence(Basnet et al., 2003), on how SCMP yield performance gains at ﬁrm level and improve thetotal supply chain performance (SCP). In addition, although some organizationshave realized the importance of implementing SCMP, they often do not know exactlywhat to implement, due to a lack of understanding of what constitutes a comprehensiveset of SCMP (Li et al., 2006b) especilly in emerging markets. For instance, in the case ofthe semiconductor industry in Malaysia, Rajagopal et al. (2009a) discussed on why
BIJ ﬁrms were reluctant to focus on supply chain partnering despite its importance for18,6 performance. Furthermore, given the failure of so many SCMP efforts to yield the desired improvements in performance, the question remains whether SCMP can positively impact performance (Handﬁeld and Nichols, 1998; Tan et al., 1999) especially in countries that are still developing. This study describes a research effort that addresses these questions. The study has a single main underlying purpose that is to disclose the836 interrelationships among the two main constructs; SCMP and SCP. Accordingly, the main research question is of whether the SCMP affect SCP. The theoretical gaps this study addresses are of importance because the SCMP construct developed in this study incorporates combination of new dimensions of SCMP. For instance, due to the lack of understanding on other dimensions of SCMP, Li et al. (2006b) suggest future research to use additional dimensions like agreed supply chain leadership. This study identiﬁed new dimensions of SCMP which combines components of SCMP proposed by Li et al. (2006b) (comprehensive model) and Min and Mentzer (2004) (system approach model). In addition, to our knowledge, there are only a limited number of studies (Kim et al., 2006; Rai et al., 2006; Wu et al., 2006; Zolait et al., 2010) available for examining the issue using the resource-based view (RBV) that emphasize the role of ﬁrms’ capability and competence. Studies using RBV in the context of SCM is also limited to examining only the link between information technology (IT) and SCM performance ( Jean et al., 2008). Therefore, this study proposes linking the SCMP and SCP using RBV as the underpinning theory. In addition to the above motivation, apparently, studies on the issues for emerging countries are limited and there is no published studies on comprehensive SCMP in Malaysia, particularly in manufacturing industry. To date, the limited research conducted in the area of SCMP were largely concerning countries such as New Zealand (Basnet et al., 2003), Pakistan (Bhutta et al., 2007), Hong Kong (Chin et al., 2004), the USA (Gowen and Tallon, 2003; Hong and Jeong, 2006), the UK (Holt and Ghobadian, 2009), and Turkey (Koh et al., 2007). Despite lacking developing countries’ case study, there are several other reasons that prompted this study to focus on Malaysia, speciﬁcally the electronics industry. The electronics manufacturing industry contributed over a quarter of manufacturing value added and over 50 percent of manufactured export in Malaysia over the period of 1980-2005 (Chandran, 2010). Owing to a small domestic market, electronics manufacturing is always driven by the export market through global orientation. Since the 1970s, electronics industries in Malaysia have also managed to attract huge amount of foreign direct investment. Now with the relocation of multinational corporations (MNCs), learning among local ﬁrms with respect to SCMP has especially improved among ﬁrms that have desires to beneﬁt by integrating into the global supply chain. However, despite a long and steady reputation of electronics manufacturing, effort to embed high-tech environment and large-scale innovation is still moderate and slow. Thus, the notion that SCMP will signiﬁcantly contribute to SCP should not be taken for granted without empirically testing the relationship. As such, Malaysia offers an interesting case for a middle income economies to examine the SCMP and its relationship to the performance. The remainder of the study is organized as follows. Section 2 outlines the main conceptual issues on SCMP and SCP. Section 3 describes the research model and explicates the theoretical basis for the hypotheses development. Sections 4 and 5 describes the research methodology and reports the results, respectively. Section 6 presents the discussion and the conclusions.
2. Main conceptual issues Supply chain2.1 SCM practices managementSCMP are viewed from a variety of different perspectives and multi-dimensionalconcept. SCMP have been deﬁned as the set of activities undertaken in an organization practicesto promote effective management of its supply chain. Pioneering research conductedby Donlon (1996) describes the SCMP to include supplier partnership, outsourcing,cycle time compression, continuous process ﬂow, and IT sharing. Tan et al. (1998a) 837empirically assessed the inclusion of purchasing, quality, and customer relationsdimensions to represent SCMP. Tan (2001) also recommended that SCMP to include theﬂow of materials and information and postponement (POS) strategy and masscustomization. Similarly, Tan et al. (2002) identify six other dimensions of SCMPthrough factor analysis namely supply chain integration, information sharing (IS),supply chain characteristics, customer service management, geographical proximity,and just-in-time capability. Chen and Paulraj (2004) use supplier-base reduction,long-term relationship, communication, cross-functional teams, and supplierinvolvement to measure SCMP. In addition, Min and Mentzer (2004) identify theconcept SCMP through system approach which includes dimensions such as agreedvision and goals, IS, risk and reward (RR) sharing, co-operation, process integration,long-term relationship, and agreed supply chain leadership. Subsequently, realizingthe importance of the SCMP, Li et al. (2005) conceptualizes, develops, and validates sixdimensions (strategic supplier partnership (SSP), customer relationship (CR), IS,information quality (IQ), internal lean practices, and POS) of SCMP and conducteda test on its relationship with the ﬁrms competitive advantage and performance(Li et al., 2006b). In reviewing and consolidating the literature, two important conceptsare identiﬁed to develop the total SCMP which will be able to structure completemulti-dimensional practices, comprising seven constructs. The seven constructsconstitute the combination of comprehensive model (Li et al., 2006b, 2005) and systemapproach model (Min and Mentzer, 2004). In other words, the proposed total SCMP inthis study will cover all the important dimensions such as upstream (SSP) anddownstream (CR) sides of a supply chain, information ﬂow across a supplychain (IS and IQ), internal supply chain processes (POS), and system approach(Min and Mentzer, 2004) that includes agreed vision and goals and risk and awardsharing.2.2 Supply chain performancePerformance measurement has been deﬁned as a systematic process of effectively andefﬁciently quantifying a concept or an action (Neely et al., 1997). In SCM, performancemeasurement enables collaborative integration among the supply chain partners. Inaddition, there are short-term objectives of SCM (enhance productivity and reduceinventory and lead time) and long-term objectives (increase market share andintegration) (Li et al., 2006b; Lyons et al., 2004). The traditional methods focus solely onwell-known ﬁnancial measures, which are best, suited to measure the value of simpleSCM applications. Unfortunately, evaluation methods that rely on ﬁnancial measuresare not well suited for newer generation of SCM applications. As such, a balancedapproach to evaluate SCP is needed to measure the short- and long-term objectives thatincludes ﬁnancial and non-ﬁnancial aspect. Based on this discussion, in this study,following Koh et al. (2007) wider approach is adopted to measures SCM-related
BIJ organizational performance. The construct measurements incorporate items that relates18,6 to sales growth, costing accuracy, and coordination between department, supplier, and customer. 2.3 SCMP and performance838 Kim et al. (2006) stated that supply chain efﬁciency can only be realized through the various interaction of SCMP. This view is supported by others studies (Dawe, 1994; Ballou, 1992) and consensus emerged in that SCMP should shift from function to integrative in order to value its performance effectiveness. Speciﬁcally, Kim et al. (2006) provided empirical evidence to show how SCMP could potential enhance organization’s competitive capabilities such as cost leadership, customer service, and product differentiation. Recent studies (Koh et al., 2007; Li et al., 2005, 2006b) also indicated that the SCMP have a common goal of ultimately improving organizational performance. For instance, Koh et al. (2007) identiﬁed that SCMP have signiﬁcant direct positive impact on organizational performance event in small and medium enterprises. As a whole, previous literature forms a strong consensus on the positive link between SCMP and SCP. 3. Research model and hypotheses Figure 1 shows the framework of the study. The framework proposes that implementation of SCMP, in electronics manufacturing industry, to inﬂuence the SCP. The inﬂuence of seven critical dimensions of SCMP on SCP namely supplier strategic, CR, IS, IQ, POS, agreed vision and goals, and RR sharing were examined. Consequently, based on the extent literature, the following sections discus the RBVs, the proposed relationships between SCMP and SCP, and the hypotheses of this study. Likewise, Section 4 discusses the construct measurements for the proposed framework. Supplier Strategic Partnership Customer Relationship Information Sharing Supply Chain Performance Information Quality Postponement Agreed Vision & GoalsFigure 1. Risk & RewardFramework of study Sharing
3.1 RBV and SCMP capability Supply chainThe underpinning theory for the research framework is the RBVs of ﬁrm. managementRBV emphasizes the role of the ﬁrms’ internal and external resources for performance(Barney, 1991). Firm resources include assets, capabilities, organizational processes, practicesﬁrm attributes, information, and knowledge (Barney, 1991). The unique bundle ofresources owned by ﬁrms that are heterogeneous is expected to explain the variation inﬁrm performances (Penrose, 1959; Wernerfelt, 1995). These resources include 839organizational capability (Praest, 1998) as well as the ﬁrms’ basic competence anddynamic capability such as coordination of different types of knowledge and integrationof multiple ﬂow of technology (Prahalad and Hamel, 1990). One important form ofcapability is the SCM capability, i.e. SCMP capability (Sari, 2008; Trkman et al., 2007;Maheshwari et al., 2006; Sanchez-Rodrıguez et al., 2005). Wu et al.(2006) stressed thatsupply chain capabilities as a unique set of organizational capabilities and proposed foursuch capabilities namely, information exchange, coordination with partners, integrationability, and supply chain responsiveness. In this context, supply chain capabilities isviewed as the ability of the ﬁrms in identifying, utilizing and assimilating information,and resources to facilitate the SCP (Wu et al., 2006). In this study, similar to the RBV deﬁnition of capability, SCMP are viewed as theﬁrms’ ability or potential ability to form SSP, establish CR and ability to shareinformation, vision, goals, and risks. In other words, this study conceptualizes SCMPas the supply chain capability to include the seven main constructs mentioned in theproposed framework. These capabilities can also be viewed as business coordinationand integration processes that are important to utilize the resources. As such,organizations embarking on supply chain need to focus on the ability of organizationalskills and processes in practicing those elements of SCMP. Thus, organizations thathave better SCMP are likely to develop a competitive advantage. Recent studies usingRBV in the context of SCM include Kim et al. (2006), Rai et al. (2006), Wu et al. (2006)and Zolait et al. (2010). These studies, although limited in the context of emergingmarkets, provide interesting accounts on the use of RBV in the context of IT, supplychain capability, and SCP. These studies also conﬁrm that IT capability facilitates theSCP. Our study emphasizes RBV from the capability centric lens that focuses mainlyon SCMP as the main capabilities of ﬁrms. 3.1.1 Strategic supplier partnership. SSP is deﬁned as the long-term relationshipdesigned to leverage the strategic and operational capabilities of individualparticipating organization to achieve signiﬁcant beneﬁts to each party (Li et al.,2006b, 2005). A true supplier partnership, encourages mutual planning and problemsolving efforts (Gunasekaran et al., 2001), and is critical in operating a leading-edgesupply chain. Azar et al. (2009) have investigated the impact of supplier management onthe performance and have found that effective supplier management is directly related tohigher level of performance conformance. Similarly, Boddy et al. (2000) and Bordonabaand Cambra (2009) also viewed supply chain partnering (which is the broader concept ofsupplier strategic partnering) as crucial asserting that such strategic collaboration willdeﬁnitely enhance performance among supply chain collaborative partners. From theRBV perspective, SSP is viewed as the ﬁrm’s ability to coordinate and integrateresources with their respective partners. Grifﬁth and Harvey (2001) consideredthe ability to coordinate inter-organizational relationships effectively as one of theimportant resources of the ﬁrms. Wu et al. (2006) views SSP as one of the key supply
BIJ chain capability and refers SSP to the ability in coordinating the partner’s18,6 transaction-related activities. These capabilities improve operational efﬁciency and performance between the partners. Similarly, proponents of RBV viewed the ability to integrate strategies in an effort to jointly execute a collective activity as an important capability (Grant, 1996). In a similar notion, SSP represents this ability. Hence, strategic partnering with suppliers will be able to enhance the supply chain efforts to better840 performances. The following hypothesis was developed on this premise: H1. The SSP has positive relationship with SCPs. 3.1.2 Customer relationship. CR is deﬁned as the practice to manage customer complaints, build long-term relationships with customers, and improve customer satisfaction (Tan et al., 1998b). Close CR allows an organization to differentiate its product from competitors and dramatically extend the value it provides to its customers and sustain customer loyalty through customer satisfaction (Cox, 2004; Dadzie and Winston, 2007). RBV views dynamic capability of the ﬁrms in terms of reconﬁguration of resources to meet evolving customer demands (Zahra and George, 2002). The ability to learn from customers and integrate with customers is a unique form of ﬁrm capability. The ability to respond to customers’ changing demands also helps ﬁrms create new products and processes. Therefore, maintaining good CR and getting customer feedback represents valid dimensions of SCMP. This construct also captures the capability notion of RBV. Analyzing the empirical data collected from Hong Kong, Chin et al. (2004) have identiﬁed that maintaining effective CR will be able to promote open communication among members of supply chain and eventually engage in joint problem solving effort with long-term commitment. Therefore, customer relation practices can bring signiﬁcant impact in managing the total value chain entities across the supply chain in order to improve the performance of the total supply chain. Based on the above discussion, this study consequently proposes the following hypothesis: H2. The CR has positive relationship with SCPs. 3.1.3 Information sharing. IS refers to the extent to which critical and proprietary information is communicated among supply chain members with regards to market, product, and customer information (Mentzer et al., 2001; Li et al., 2006a). The RBV emphasize on the ability of ﬁrms in generating new knowledge and ability in facilitating IS. Knowledge acquisition, assimilation, transformation, and exploitation which are termed as absorptive capacity in the RBV literature are important dimensions of organizational capability. Therefore, IS with partners is considered as important elements of supply chain capability. Wu et al. (2006) conceptualized information exchange as one of the constructs representing supply chain capabilities. The effort in providing information and making it visible to other parties in the supply chain allows for faster and accurate business decisions that translates as a source of competitive advantage (Moberg et al., 2002). As such, IS is regarded as the terminator of “bullwhip effect” (Fiala, 2005) that reduces the total cost of the supply chain in delivering efﬁcient SCP (Gavirneni, 2006). This study therefore proposes the following hypothesis: H3. The IS has positive relationship with SCPs. 3.1.4 Information quality. IQ refers to the extent of which the information ﬂow and exchange is accurate, timely, adequate, and credible (Li et al., 2006b). Numerous studies
(Li et al., 2006a; Lyons et al., 2004; Moberg et al., 2002) have shown that well-managed Supply chainIQ within and across the organization will directly lead to improved SCP. Further, managementForslund and Jonsson (2007), through their recent research, have indicatedthat different IQ deﬁciency could impact the usefulness of forecast and its ability to practicesinﬂuence SCP. Hence, this will also provide managers to make precise businessdecision for effective management of supply chain (Raisinghani and Meade, 2005).Based on this assumption, the following hypothesis was developed: 841 H4. The IQ has positive relationship with SCPs.3.1.5 Postponement. POS is deﬁned as the practice of moving forward one or severaloperations or activities to a much later point in the supply chain (Beamon, 1998). Fromthe RBV standpoint, POS capability characterize the organizational and strategicroutines of ﬁrms by which they achieve new resources conﬁguration especially inpostponing manufacturing activities to meet changing market conditions. Increasingly,POS has become a manufacturing strategy at ﬁrm level (Yeung et al., 2007). POS enablesan organization to meet a high level of product customization through productionﬂexibility (Hoek et al., 2001). Inventories are kept undifferentiated for a certain perioduntil customer demand is certain. Hence, this enables an organization to be highlyresponsive towards change in customer demand (Li et al., 2005, 2006b). Yang et al. (2010)compared the translating implementation of manufacturing POS to service POS and itsbeneﬁt to members of the supply chain in total. Overall, POS can reduce inventory costalong the supply chain and eventually increase SCP (Yang et al., 2007). Based on existingwork, this study consequently proposes the following hypothesis: H5. POS has positive relationship with SCPs.3.1.6 Agreed vision and goals. Successful and effective chain requires collaborationamong partners (Boddy et al., 2000; Lambert et al., 1998). This collaboration is obtainedthrough IS, trust, and commitment. Unfortunately, this cannot be achieved withoutagreed vision and common goals (VIGOAL) among members of the supply chain(Spekman et al., 1998). RBV emphasize the need to develop capability in the forms ofintegrating strategies and coordinating collective activities between partners. Agreedvision and goals capture such forms of capability. Several authors (Cooper andEllram, 1993; Cooper et al., 1997a, b) concur strongly on the fact that agreed vision andgoals are the key component of SCM. Therefore, agreed vision and goals are imminentto orchestrate the roles and responsibilities of the supply chain members. Subsequently,this will ensure the success of supply chain practices in capturing a high level of SCP(Wisner, 2003). As discussed, this study proposes the following hypothesis: H6. Agreed vision and goals have positive relationship with SCPs.3.1.7 RR sharing. The term risk is deﬁned as the extent to which there is uncertaintyabout whether potentially signiﬁcant or disappointing outcomes of decisions(Finch, 2004). What most deﬁnitions of risk have in common are the three dimensions(Juttner, 2005): (1) likelihood of occurrence of a particular event or outcome; (2) consequences of the particular event or outcome occurring; and (3) causal pathway leading to the event.
BIJ Previous studies (Cooper and Ellram, 1993; Cooper et al., 1997a, b) regarded the RR18,6 sharing among the supply chain partners as a collective effort in managing SCM. The capability to share RR will help to divide the level of risk and return between strategic partners on technology, customer, or market-focused initiatives (Hall, 1999; Ritchie and Brindley, 2007) whereby, it provides trustworthy and coordinated relationship partnering among members of supply chain. As a result, RR sharing practices act as an842 impetus for effective supply chain (Ellram and Cooper, 1990). Consequently, in the long run, this will be able to improve the SCP (Towill, 2005). Therefore, the following hypothesis was developed: H7. RR sharing has positive relationship with SCPs. 4. Research methodology 4.1 Development of the survey instrument The questionnaire for this study consisted of three main sections, namely the background of the company, the motivation, and implementation of SCMP and speciﬁc questions designed to measure the SCP constructs. A total of seven-dimensional constructs (Table I) perceived to be important for effective SCMP were proposed to represent the SCMP. Construct measuring SSP, CR, IS, IQ, and POS follows Li et al. (2005, 2006a, b). As mentioned earlier, following Min and Mentzer (2004) and Bowersox et al. (1999), we included two other dimensions of SCMP namely, agreed vision and goals, and RR sharing. Overall, this new SCMP are measured by considering SCMP from within the whole system of supply chain that includes upstream, downstream, internal process, across supply chain, and system orientation. Hence, the new SCMP could be viewed as a more comprehensive concept in comparison to the narrow view taken in previous researches (Alvarado and Kotzab, 2001; Basnet et al., 2003). All items of SCMP are measured using seven-point scales ranging from “strongly disagree” to “strongly agree”. Likewise, construct measuring dimensions of SCP were adopted from Koh et al. (2007). We use a seven-point scale as a unit of measurement ranging from “deﬁnitely worse” to “deﬁnitely better” in relative to their major competitor. The collective evidence from past literatures (Li et al., 2005, 2006b; Min and Mentzer, 2004; Bowersox et al., 1999; Koh et al., 2007) suggested that the SCMP and SCP constructs demonstrate good measurement properties. Table I summarizes the variables and number of measurement items and supporting literature for each measurement variable. In addition, the questionnaire was pre-tested by two professionals in practice for accuracy and validity of the question interpretation (content validity). Based on the opinions of the professionals and signiﬁcant support from the previous literatures we ﬁnd that the measurement fulﬁll the content validity and clarity of content. 4.2 The sample A total of 600 electronics ﬁrms were randomly selected from the Information Service of Statistical Department, Malaysia. The survey, through the mailed questionnaire, was carried out for a period of six months in early 2009. As a measure to speed up and improve response rate, follow-up calls with a promised presentation of ﬁndings to respective ﬁrms for managerial insights yielded encouraging results. However, only when there is no signiﬁcant difference between the initial respondents and respondents
Supply chain NumbersConstruct Description of items Sample survey question Source managementSSP A long-term relationship 6 We regularly solve Li et al. practices designed to leverage the problems jointly with our (2005, 2006a, b) strategic and operational suppliers capabilities of individual 843 participating organization to achieve signiﬁcant beneﬁts to each partyCR A practices to manage 5 We frequently measure and Li et al. customer complaints, build evaluate customer (2005, 2006a, b) long-term relationships with satisfaction customers, and improve customer satisfactionIS IS refers to the extent to 6 Our trading partners keep Li et al. which critical and us fully informed about (2005, 2006a, b) proprietary information is issues that affect our communicated to among business supply chain members with regards to market, product, and customer informationIQ IQ refers to the extent of 5 Information exchange Li et al. which the information ﬂow between our trading (2005, 2006a, b) and exchange is accurate, partners and us is timely timely, adequate, and crediblePOS POS is deﬁned as the 4 We delay ﬁnal product Li et al. (2005, practice of moving forward assembly activities until 2006a, b) one or several operations or customer orders have activities to a much later actually been received point in the supply chainVIGOAL An effort to establishing 4 Our supply chain members Min and commonly agreed vision have common, agreed to Mentzer (2004) among supply chain goals for SCM and partners to achieve speciﬁc Bowersox et al. common objectives (1999)RR sharing A mutual sharing of risk 3 Our supply chain members Min and factors and reward factors share risks and rewards Mentzer (2004) among members of supply and chain Bowersox et al. (1999)SCP A performance measure 5 How did your business Koh et al. (2007) which enhances short-term perform over the last three goals (reduce cost) and long- years relative to their major term goals (increase market competitors in terms of Table I. share and integration) increase in sales? Variable measurementafter the follow-up calls, will the ﬁndings be representation of the population. We testedfor such difference between the groups but were unable to ﬁnd any signiﬁcantdifferences. Finally, after eliminating incomplete survey, there were 110 completeand useable responses, representing a response rate of 18 percent. Demographic datashowed in Table II depict that majority (60.3 percent) of the ﬁrms represent
BIJ Business description % Number of employees %18,6 Component 60.3 Fewer than 50 – Industrial electronics 22.3 50-100 13.2 Consumer electronics 17.4 101-250 18.4 251-500 39.5 501 or greater 28.9844 Annual sales (million) % Operating experience (years) % Less than 1 – Less 1 – 1-5 18.4 1-5 5.3 5-10 23.7 6-10 13.2Table II. 10-50 34.2 10-15 years 39.5Description of the 50-100 15.8 15-20 years 34.2sampled ﬁrms More than 100 7.9 More than 20 years 7.8 the component electronics industry. In terms of employment size the majority of the ﬁrms are in the category of 251-500 workers and greater. Almost 73 percent of the selected ﬁrms have between 10 and 20 years of operational experience. 4.3 Analytical procedures and variable measurements Data processing involve two stages. In the ﬁrst stage, descriptive statistics was employed to identify the characteristics of the sampled ﬁrms. The second stage involved estimating the measurements validity and reliability, structural parameters of the structural equation model, and testing the research hypotheses using the partial least squares (PLS) method (Chin et al., 2003). PLS method were preferred over the better-known LISREL method because its structural equation model allowed us to test the research model and, at the same time, assess the properties of the underlying empirical model. PLS has enjoyed increasing popularity in recent years because of its ability to model latent construct under the conditions of non-normality and ability of testing the theoretical framework partially without needing to fully crystallize the model (Chin, 1998). PLS is known to be particularly advantageous in the initial development and assessment phase of theory building (Fornell and Bookstein, 1982). Furthermore, the PLS method is more robust since its does not require either a large sample or a normally distributed data (Fornell and Larcker, 1981). Convergent validity indicates the extent to which the measures of a construct that are theoretical related are also related in reality. Convergent validity can be evaluated by inspecting the factor loadings of the measures on their respective constructs (Chin, 1998; Hulland, 1999), and the reliability of the measures can be assessed using composite reliability and average variance extracted (AVE). Table III shows the results of the psychometric properties of the measurements. Most of the factor loading are satisfactory with the cutoff value above 0.7, except that the factor loading of two items are below the cutoff value but yet acceptable. Thus, overall measurement items have adequate item reliability. Similarly, for convergent validity (also referred to as composite reliability), the AVE should be at least 0.5 and the CR should be greater than 0.6 (Bagozzi and Yi, 1988). In all cases, the measurement model seems to have adequate convergent validity and reliability. Discriminant validity can be veriﬁed with the square root of the AVE for each construct higher than any correlation between this construct and any other construct
Supply chainConstruct and items Loading SE t-valueSSP, a ¼ 0.789, CR ¼ 0.869, AVE ¼ 0.693 managementOrganization considers quality as number one criterion in selecting practicessuppliers 0.906 0.011 81.223Organization regularly solve problems jointly with its suppliers 0.900 0.009 90.345Organization helps its suppliers to improve their product quality 0.851 0.055 9.976Organization has continuous improvement programs that include its 845key suppliers 0.615 0.125 6.991Organization include its key suppliers in its planning and goal settingactivities 0.775 0.068 7.773Organization actively involves its key suppliers in new productdevelopment processes 0.777 0.033 8.855CR, a ¼ 0.655, CR ¼ 0.787, AVE ¼ 0.692Organization frequently interacts with customers to set its reliability,responsiveness, and other standards 0.815 0.048 17.022Organization frequently measures and evaluates customer satisfaction 0.804 0.054 15.989Organization frequently determine future customer expectations 0.811 0.039 18.765Organization facilitates customers’ ability to seek assistance from it 0.885 0.044 17.567Organization periodically evaluates the importance of its relationshipwith its customers 0.877 0.066 14.897IS, a ¼ 0.774, CR ¼ 0.839, AVE ¼ 0.637Organization informs its trading partners in advance of changingneeds 0.913 0.023 36.659Organization’s trading partners share proprietary information withyour organization 0.768 0.065 18.222Organization’s trading partners keep your organization fully informedabout issues that affect its business 0.816 0.044 21.677Organization’s trading partners share business knowledge of corebusiness processes with your organization 0.749 0.066 18.678Organization and its trading partners exchange information that helpsestablishment of business planning 0.782 0.053 14.750Organization and its trading partners keep each other informed aboutevents or changes that may affect the other partners 0.668 0.095 9.878IQ, a ¼ 0.742, CR ¼ 0.825, AVE ¼ 0.707Information exchange between organization and its trading partnersis timely 0.825 0.055 12.544Information exchange between organization and its trading partnersis accurate 0.742 0.023 14.893Information exchange between organization and its trading partnersis complete 0.882 0.047 12.672Information exchange between organization and its trading partnersis adequate 0.767 0.036 14.436Information exchange between organization and its trading partnersis reliable 0.876 0.062 12.725POS, a ¼ 0.615, CR ¼ 0.773, AVE ¼ 0.834Organization’s products are designed for modular assembly 0.928 0.453 2.833Organization delays ﬁnal product assembly activities until customerorders have actually been received 0.743 0.339 2.987Organization delays ﬁnal product assembly activities until the last Table III.possible position (or nearest to customer) in the supply chain 0.777 0.375 2.118 Psychometric propertiesVIGOAL, a ¼ 0.789, CR ¼ 0.869, AVE ¼ 0.611 of measuresSupply chain members have common, agreed goals for SCM 0.711 0.044 17.342 of independent and (continued) dependent variables
BIJ Supply chain members are actively involved in standardizing supply18,6 chain practices and operations 0.881 0.021 15.999 Supply chain members clearly deﬁne roles and responsibilities of each others cooperatively 0.834 0.027 15.611 Know which supply chain members are responsible for what activity within the supply chain 0.772 0.032 16.912846 RR sharing, a ¼ 0.819, CR ¼ 0.864, AVE ¼ 0.654 Supply chain members share risks and rewards 0.838 0.439 6.839 Supply chain members share research and development costs and results with each other 0.745 0.375 7.566 Supply chain members help each other ﬁnancial capital investment 0.766 0.411 7.198 SCP, a ¼ 0.789, CR ¼ 0.869, AVE ¼ 0.803 More accurate costing 0.917 0.023 28.871 Increase in coordination between departments 0.967 0.009 34.082 Increase in coordination with suppliers 0.866 0.016 31.593 Increase in coordination with customers 0.867 0.021 29.822Table III. Increase in sales 0.948 0.011 30.899 (Fornell and Bookstein, 1982; Fornell and Larcker, 1981). As shown in Table IV, each construct shares a greater variance with its own measures than with any other construct. This reveals that each construct is more closely related to its own measures than to those of other constructs and thereby conﬁrming the discriminant validity (Fornell and Bookstein, 1982; Fornell and Larcker, 1981). 5. Results In this section, we discuss the current SCMP among electronics ﬁrms in Malaysia followed by the empirical results. Limited studies are available on the current SCMP for the electronics industry in Malaysia. Nevertheless, these studies reveal that SCMP are indeed signiﬁcantly undertaken by MNCs and its suppliers especially in electrical and electronics industry. Rajagopal et al. (2009a) using a case study approach highlighted the efforts in improving supplier’s relationship, IS, and CR in two MNCs and among its suppliers. However, the study also cautions that the level of SCMP differs between the MNCs. Lacking the empirical evidence on the detail SCMP for the entire electronics industry, we ﬁrst discuss the current state of SCMP in the electronics industry in Malaysia. Table V reports the mean values of all dimensions of SCMP. SSP CR IS IQ POS VIGOAL RR SCP SSP 0.832 CR 20.129 0.832 IS 0.201 0.083 0.798 1Q 0.178 0.037 0.372 0.841 POS 0.377 0.016 0.267 0.400 0.913 VIGOAL 0.307 20.134 0.378 0.277 0.299 0.781 RR 0.276 0.177 0.114 0.267 0.323 0.416 0.809 SCP 0.112 20.023 0.247 0.223 0.369 0.488 0.487 0.927Table IV.Correlations between Note: The italics items on the diagonal represent the square roots of the AVE, and off-diagonalconstructs elements are the correlation estimates
The results indicate that mean scores of SSP, IQ, and IS are much higher compared to Supply chainother dimensions of SCMP. Relatively, mean scores of CR and PST were the lowest, managementindicating a lack in the use of such practices. However, consumer electronics ﬁrmshave relatively higher CR scores than component and industrial electronics ﬁrms. This practicesis consistent with previous studies (Rajagopal et al., 2009a; Omar et al., 2009;Sambasivan and Jacob, 2008) that highlighted the signiﬁcant use of many of the SCMPamong electronics ﬁrms in Malaysia. As a whole, we can conclude that electronics 847ﬁrms in Malaysia are inclined to engage in SCMP. The electronics industry in Malaysiais driven by few large MNCs that are export oriented. These MNCs increasingly engagein SCMP to form a global supply chain (Sambasivan and Jacob, 2008) and also requireits suppliers (including local suppliers and producers) to do the same. Indeed, SCM isseen as a tool to cope with intense competition and pressure to bring the product tomarket faster (Rajagopal et al., 2009a). The government’s incentives and support alsoprepares local industries to adopt SCM in Malaysia (Rajagopal et al., 2009b). We used a bootstrapping procedure to test the effects and the statistical signiﬁcanceof the parameters using t-test in the structural model (Chin, 1998). The varianceexplained (R 2) and the signiﬁcance of the path coefﬁcient indicates the quality of PLSmodel (Chin, 1998; Saade, 2007). Table VI shows the results of the model. The R 2 value ´was 0.469 and it indicates that the model explains a good amount of variance in SCP. Theresults provide signiﬁcant support for some of the hypotheses proposed in this study.SSP, IS, IQ, POS, agreed vision and goals, and RR sharing were found to have signiﬁcantpositive effects on SCP. However, CR, although positive, lacks the signiﬁcance.Managing CR require ﬁrms to extensively invest in enabling technology that supports Electronics (overall) Component Industrial ConsumerConstruct Mean SD Mean SD Mean SD Mean SDSSP 5.84 0.56 5.84 0.54 5.85 0.65 5.80 0.55CR 3.92 0.76 3.92 0.78 3.73 0.89 4.10 0.46IS 5.20 0.99 5.15 0.91 5.24 1.25 5.27 0.94IQ 5.97 0.85 6.05 0.71 5.75 1.15 5.91 0.91POS 3.68 0.83 3.71 0.73 3.45 0.95 3.83 0.25VIGOAL 5.41 0.29 5.39 0.57 5.43 0.90 5.46 0.56 Table V.RR 5.17 0.98 5.20 1.15 4.94 0.96 5.33 0.43 SCMP in electronicsSCP 5.28 0.87 5.24 0.84 5.37 1.14 5.30 0.57 industry in MalaysiaDimensions Path coefﬁcient (b) t-value HypothesesSSP 0.104 * 2.216 SupportedCR 0.013 0.355 Not supportedIS 0.176 * * 2.745 SupportedIQ 0.125 * * 2.978 SupportedPOS 0.014 * 0.598 SupportedVIGOAL 0.377 * * * 7.459 Supported Table VI.RR 0.144 * * 2.416 Supported Results of the PLS analysis (pathNote: *p-value , 0.01, * *p-value , 0.05, and * * *p-value , 0.001, respectively coefﬁcients, t-values)
BIJ customer interactions with ﬁrms ( Jean et al., 2008). Challenges in effective18,6 implementation of such technology may have limited the building of better CRs that reduces its signiﬁcance. Moreover, CR may also have an indirect effect on SCP moderated by technological initiatives (Jean et al., 2008). Indeed, Rajagopal et al. (2009a) lucidly argued on the role of technology in enabling SCMP in two electronics MNCs in Malaysia. In fact, it should be noted that the beneﬁts of all SCMP, in this study, could have been848 potentially more signiﬁcant if ﬁrms pose considerable IT capabilities ( Jean et al., 2008). We suggest that future studies in emerging markets consider the impact of IT in facilitating the SCMP towards achieving greater performance. Agreed vision and goals (b ¼ 0.377, p , 0.001), are the most inﬂuential factors in determining the SCP suggesting that VIGOAL is a powerful predictor of SCP. For instance, in Malaysia several ﬁrms share common goals like enabling the notiﬁcation of shipping documentation via RosettaNet. This has enabled members of the supply chain to electronically correspond shipping documentation to the local customs ofﬁcials. The established mutual goals beneﬁted all within the system. Agreed goals also create mutual participation via planned collaboration and co-operation. When one ﬁrm moves to achieve its goals, the other member of the supply chain should do the same. Other factors having greater effects include IS (b ¼ 0.176, p , 0.01), RR sharing (b ¼ 0.144, p , 0.01), and IQ (b ¼ 0.125, p , 0.01). Similar to previous studies ( Jayaram et al., 2000; Mason-Jones and Towill, 1999), IS and IQ are found to be signiﬁcant factors in enhancing the SCP of electronics ﬁrm in Malaysia. Additionally, Zhou and Benton (2007), also supported the proposition that good information management can lead to right supply chain practices and eventually create an effective and efﬁcient supply chain. The ﬁndings of this study also concurs with the studies from Cooper and Ellram (1993), Cooper et al. (1997a, b) that there is signiﬁcant relationship between RR sharing practices and performance. 6. Discussion and conclusion This study has provided empirical justiﬁcation for a framework that identiﬁes seven constructs of SCMP and describes the relationship among SCMP and SCP within the context of electronics manufacturing in Malaysia. Previous studies supporting the importance of SCMP mostly used case studies and relate SCMP to organizational performance and not SCP. The major contribution of the present study is the development of a set of SCMP constructs through comprehensive combination and, accordingly, examining its impact on SCP. Based on a survey data of 110 electronics manufacturing ﬁrms, the research framework was tested using PLS method, which is a variance-based structural equation modeling approach. This study carries more weight especially for generalization purpose due to the limited quantitative approach in the extant literatures. As a whole, effective SCMP have important implications for SCP. This study offers a number of managerial implications. First, it provides SCM managers with an impeccable formula for evaluating the effectiveness of the new combination of SCMP. Second, the analysis also indicates that SCMP might directly inﬂuence SCP. Theoretically, this study offers empirical evidence suggesting that even in emerging markets better SCMP can yield good performance. These ﬁndings offer scholars new avenues for future research and consequently provide managers important insights on the effectiveness of SCMP. In the long term, the success of electronics manufacturing ﬁrms in Malaysia are heavily dependent on its
strategic supply chain factors such as agreed vision and goals, RR sharing, IS, and IQ. Supply chainAs such this study, inline with (Chandra and Kumar, 2000) concludes that the entire managementvalue chain along the upstream and internal process of the supply chain has to beeffective. Since there are practices which are not consistent in their impact towards practicesSCP, for instance customer relation, there is a need to test this practice for any indirectimpact on SCP. However, this test will need to take consideration of the role ofmediating effects of other variables such as IT initiatives, supply chain integration, 849or supply chain competitiveness. Apart from this, future research can also considerstudying the synergies between total quality management practices and knowledgemanagement as well as measuring how practices of other disciplines in combinationwith SCMP could affect the performances of supply chain. Future research can alsofocus on expanding the research scope to different industries or investigate thecomparative implementation situations between different industries in terms of typesof business operations, ownership, and ﬁrm sizes. Among the limitations of this study is the use of only one informant per ﬁrm, whichmight be a cause for possible response bias. Thus, caution should be exercised wheninterpreting the results. Future research should endeavor to collect data from multiplemembers across the supply chain. Furthermore, this study reports from a questionnairesurvey at one point in time and lacks trends or changes. Since only the electronics industrywas considered, the conclusive evidence reported in this study is also industry speciﬁc.Despite these limitations, however, the new insights of this study could potentially inspirefurther empirical work within this area especially in emerging markets.Notes 1. Details of the items measuring each construct are reported in Table III. 2. Data not reported due to space constraint but can be made available upon request.ReferencesAlvarado, U.Y. and Kotzab, H. (2001), “Supply chain management: the integration of logistics in marketing”, Industrial Marketing Management, Vol. 30 No. 2, pp. 183-98.Azar, A., Kahnali, R.A. and Taghavi, A. (2009), “Relationship between supply chain quality management practices and their effects on organisational performance”, Singapore Management Review, Vol. 32 No. 1, pp. 45-68.Bagozzi, R.P. and Yi, Y. (1988), “On the evaluation of structural equation models”, Journal of the Academy of Marketing Science, Vol. 16 No. 1, pp. 74-94.Ballou, R.A. (1992), Business Logistics Management, Prentice-Hall, Englewood Cliffs, NJ.Barney, J.B. (1991), “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17 No. 1, pp. 99-120.Basnet, C., Corner, J., Wisner, J. and Tan, K.C. (2003), “Benchmarking supply chain management practice in New Zealand”, Supply Chain Management: An International Journal, Vol. 8 No. 1, pp. 57-64.Beamon, B.M. (1998), “Supply chain design and analysis: models and methods”, International Journal of Production Economics, Vol. 55 No. 3, pp. 281-94.Bechtel, C. and Jayaram, J. (1997), “Supply chain management: a strategic perspective”, The International Journal of Logistics Management, Vol. 8 No. 1, pp. 15-34.
BIJ Bhutta, M.K.S., Rana, A.I. and Asad, U. (2007), “SCM practices and the health of the SMEs in Pakistan”, Supply Chain Management: An International Journal, Vol. 12 No. 6, pp. 412-22.18,6 Boddy, D., Macbeth, D. and Wagner, B. (2000), “Implementing collaboration between organizations: an empirical study of supply chain partnering”, Journal of Management Studies, Vol. 37 No. 7, pp. 1003-18. Bordonaba, V. and Cambra, J. (2009), “Managing supply chain in the context of SMEs:850 a collaborative and customized partnership with the suppliers as the key for success”, Supply Chain Management: An International Journal, Vol. 14 No. 5, pp. 393-402. Boubekri, N. (2001), “Technology enablers for supply chain management”, Integrated Manufacturing Systems, Vol. 12 No. 6, pp. 394-9. Bowersox, D. J., Closs, D. J. and Stank, T. P. (1999), 21st Century Logistics: Making Supply Chain Integration a Reality, Council of Logistics Management, Oak Brook, IL. Brewer, P.C. and Speh, T.W. (2000), “Using the balanced scorecard to measure supply chain performance”, Journal of Business Logistics, Vol. 21 No. 1, pp. 75-92. Burgess, K., Singh, P.J. and Koroglu, R. (2006), “Supply chain management: a structured literature review and implications for future research”, International Journal of Operations & Production Management, Vol. 26 No. 7, pp. 703-29. Carmignani, G. (2009), “Supply chain and quality management: the deﬁnition of a standard to implement a process management system in a supply chain”, Business Process Management Journal, Vol. 15 No. 3, pp. 395-407. Carr, A.S. and Smeltzer, L.R. (1999), “The relationship of strategic purchasing to supply chain management”, European Journal of Purchasing & Supply Management, Vol. 5, pp. 43-51. Chan, F.T.S., Humphreys, P. and Lu, T.H. (2001), “Order release mechanisms in supply chain management: a simulation approach”, International Journal of Physical Distribution & Logistics Management, Vol. 31 No. 2, pp. 124-39. Chandra, C. and Kumar, S. (2000), “Supply chain management in theory and practice: a passing fad or a fundamental change?”, Industrial Management & Data Systems, Vol. 100 No. 3, pp. 100-13. Chandran, V.G.R. (2010), “Modularity, technology and performance: a study of electronics industry in penang”, unpublished PhD thesis, University of Malaya, Kuala Lumpur. Chen, I.J. and Paulraj, A. (2004), “Towards a theory of supply chain management: the constructs and measurements”, Journal of Operations Management, Vol. 22 No. 2, pp. 119-50. Chin, K.-S., Tummala, V.M.R., Leung, J.P.F. and Tang, X. (2004), “A study on supply chain management practices: the Hong Kong manufacturing perspective”, International Journal of Physical Distribution & Logistics Management, Vol. 34 No. 6, pp. 505-24. Chin, W.W. (1998), “The partial least squares approach to structural equation modeling”, in Marcoulides, G.A. (Ed.), Modern Business Research Methods, Lawrence Erlbaum, Mahwah, NJ, pp. 295-336. Chin, W.W., Marcolin, B.L. and Newsted, P.R. (2003), “A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronicmail emotion/adoption study”, Information Systems Research, Vol. 14 No. 2, pp. 189-217. Cooper, M.C. and Ellram, L.M. (1993), “Characteristics of supply chain management and the implication for purchasing and logistics strategy”, The International Journal of Logistics Management, Vol. 4 No. 2, pp. 13-24.
Cooper, M.C., Lambert, D.M. and Pagh, J.D. (1997b), “Supply chain management: more than Supply chain a new name for logistics”, The International Journal of Logistics Management, Vol. 8 No. 1, pp. 1-14. managementCooper, M.C., Ellram, L.M., Gardner, J.T. and Hanks, A.M. (1997a), “Meshing multiple alliances”, practices Journal of Business Logistics, Vol. 18 No. 1, pp. 67-89.Cox, A. (2004), “The art of the possible: relationship management in power regimes and supply chains”, Supply Chain Management: An International Journal, Vol. 9 No. 5, pp. 346-56. 851Croom, S., Romano, P. and Giannakis, M. (2000), “Supply chain management: an analytical framework for critical literature review”, European Journal of Purchasing & Supply Management, Vol. 6, pp. 67-83.Dadzie, K.Q. and Winston, E. (2007), “Consumer response to stock-out in the online supply chain”, International Journal of Physical Distribution & Logistics Management, Vol. 37 No. 1, pp. 19-42.Dale, B.G., Lascelles, D.M. and Lloyd, A. (1994), Supply Chain Management and Development, Prentice-Hall, New York, NY.Dawe, R.L. (1994), “An investigation of the pace and determination of information technology use in the manufacturing materials logistics system”, Journal of Business Logistics, Vol. 15 No. 1, pp. 229-58.Donlon, J.P. (1996), “Maximizing value in the supply chain”, Chief Executive, Vol. 117, pp. 54-63.Ellram, L.M. and Cooper, M.C. (1990), “Supply chain management, partnership and the shipper-third party relationship”, International Journal of Logistics Management, Vol. 1 No. 2, pp. 1-10.Fiala, P. (2005), “Information sharing in supply chains”, The International Journal of Management Science, No. 33, pp. 419-23.Finch, P. (2004), “Supply chain risk management”, Supply Chain Management: An International Journal, Vol. 9 No. 2, pp. 183-96.Fornell, C.R. and Bookstein, F.L. (1982), “Two structural equation models: LISREL and PLS applied to consumer exit-voice theory”, Journal of Marketing Research, Vol. 19 No. 4, pp. 440-52.Fornell, C.R. and Larcker, D.F. (1981), “Two structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.Forslund, H. and Jonsson, P. (2007), “The impact of forecast information quality on supply chain performance”, International Journal of Operations & Production Management, Vol. 27 No. 1, pp. 90-107.Gavirneni, S. (2006), “Price ﬂuctuations, information sharing, and supply chain performance”, European Journal of Operational Research, Vol. 174, pp. 1651-63.Gowen, C.R. and Tallon, W.J. (2003), “Enhancing supply chain practices through human resource management”, Journal of Management Development, Vol. 22 No. 1, pp. 32-44.Grant, R. (1996), “Prospering in dynamically-competitive environments: organizational capability as knowledge integration”, Organization Science, Vol. 7 No. 4, pp. 375-87.Grifﬁth, D.A. and Harvey, M.G. (2001), “A resource perspective on strategic of global dynamic capabilities”, Journal of International Business Studies, Vol. 32 No. 3, pp. 597-606.Gunasekaran, A., Patel, C. and Tirtiroglu, E. (2001), “Performance measures and metrics in a supply chain environment”, International Journal of Operations & Production Management, Vol. 21 Nos 1/2, pp. 71-87.
BIJ Hall, R.W. (1999), “Rearranging risks and rewards in a supply chain”, Journal of General Management, Vol. 24 No. 3, pp. 22-32.18,6 Handﬁeld, R.B. and Nichols, E.L.J. (1998), An Introduction to Supply Chain Management, Prentice-Hall, Upper Saddle River, NJ. Hoek, R.I.V., Harrison, A. and Christopher, M. (2001), “Measuring agile capabilities in the supply chain”, International Journal of Operations & Production Management, Vol. 21 Nos 1/2,852 pp. 126-47. Holt, D. and Ghobadian, A. (2009), “An empirical study of green supply chain management practices amongst UK manufacturers”, Journal of Manufacturing Technology Management, Vol. 20 No. 7, pp. 933-56. Hong, P. and Jeong, J. (2006), “Supply chain management practices of SMEs: from a business growth perspective”, Journal of Enterprise Information Management, Vol. 19 No. 3, pp. 292-302. Hulland, J. (1999), “Use of partial least squares (PLS) in strategic management research: a review of four recent studies”, Strategic Management Journal, Vol. 20, pp. 195-204. Jayaram, J., Vickery, S.K. and Droge, C. (2000), “The effects of information system infrastructure and process improvements on supply-chain time performance”, International Journal of Physical Distribution & Logistics Management, Vol. 30 Nos 3/4, pp. 314-30. Jean, B.R.-J., Sinkovics, R.R. and Kim, D. (2008), “Information technology and organizational performance within international business to business relationships: a review and an integrated conceptual framework”, International Marketing Review, Vol. 25 No. 5, pp. 563-83. Juttner, U. (2005), “Supply chain risk management-understanding the business requirements from a practitioner perspective”, The International Journal of Logistics Management, Vol. 16 No. 1, pp. 120-41. Kim, S.W. (2006), “Effects of supply chain management practices, integration and competition capability on performance”, Supply Chain Management: An International Journal, Vol. 11 No. 3, pp. 241-8. Kim, D., Cavusgil, S.T. and Calantone, R.J. (2006), “Information system innovations and supply chain management: channel relationships and ﬁrm performance”, Journal of the Academy of Marketing Science, Vol. 34 No. 1, pp. 40-54. Koh, S.C.L., Demirbag, M., Bayraktar, E., Tatoglu, E. and Zaim, S. (2007), “The impact of supply chain management practices on performance of SMEs”, Industrial Management & Data Systems, Vol. 107 No. 1, pp. 103-24. Lambert, D.M. and Cooper, M.C. (2000), “Issues in supply chain management”, Industrial Marketing Management, Vol. 29, pp. 65-83. Lambert, D.M., Cooper, M.C. and Pagh, J.D. (1998), “Supply chain management: implementation issues and research opportunities”, International Journal of Logistics Management, Vol. 9 No. 2, pp. 1-19. Li, G., Lin, Y., Wang, S. and Yan, H. (2006a), “Enhancing agility by timely sharing of supply information”, Supply Chain Management: An International Journal, Vol. 11 No. 5, pp. 425-35. Li, S., Rao, S.S., Ragu-Nathan, T.S. and Ragu-Nathan, B. (2005), “Development and validation of a measurement instrument for studying supply chain management practices”, Journal of Operations Management, Vol. 23, pp. 618-41.
Li, S., Ragu-Nathan, B., Ragu-Nathan, T.S. and Rao, S.S. (2006b), “The impact of supply chain Supply chain management practices on competitive advantage and organizational performance”, International Journal of Management Science, Vol. 34, pp. 107-24. managementLummus, R.R. and Vokurka, R.J. (1999), “Deﬁning supply chain management: a historical practices perspective and practical guidelines”, Industrial Management & Data Systems, Vol. 99 No. 1, pp. 11-17.Lyons, A., Coleman, J., Kehoe, D. and Coronado, A. (2004), “Performance observation and 853 analysis of an information re-engineered supply chain: a case study of an automotive ﬁrm”, Industrial Management & Data Systems, Vol. 104 No. 8, pp. 658-66.Maheshwari, B., Kumar, V. and Kumar, U. (2006), “Optimizing success in supply chain partnerships”, Journal of Enterprise Information Management, Vol. 19 No. 3, pp. 277-91.Mason-Jones, R. and Towill, D.R. (1999), “Using the information decoupling point to improve supply chain performance”, The International Journal of Logistics Management, Vol. 10 No. 2, pp. 13-26.Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D. and Zacharia, Z.G. (2001), “Deﬁning supply chain management”, Journal of Business Logistics, Vol. 22 No. 2.Min, S. and Mentzer, J.T. (2004), “Developing and measuring supply chain management concepts”, Journal of Business Logistics, Vol. 25 No. 1, pp. 63-99.Moberg, C.R., Cutler, B.D., Gross, A. and Speh, T.W. (2002), “Identifying antecedents of information exchange within supply chains”, International Journal of Physical Distribution & Logistics Management, Vol. 32 No. 9, pp. 755-70.Neely, A., Richards, H., Mills, J., Platts, K. and Bourne, M. (1997), “Design performance measures: a structured approach”, International Journal of Operations & Production Management, Vol. 17 No. 11, pp. 1131-52.New, S.J. (1997), “The scope of supply chain management research”, Supply Chain Management, Vol. 2 No. 1, pp. 15-22.Oliver, R.K. and Webber, M.D. (1982), “Supply-chain management: logistics catches up with strategy”, in Christopher, M. (Ed.), Logistics: The Strategic Issues, Chapman & Hall, London.Omar, R., Zailani, S. and Sulaiman, M. (2009), “Supply chain quality orientation: does company proﬁle matter?”, International Journal of Information Technology and Management, Vol. 8 No. 2, pp. 214-30.Penrose, E.T. (1959), The Theory of the Growth of the Firm, Wiley, New York, NY.Power, D.J., Sohal, A. and Rahman, S.U. (2001), “Critical success factors in agile supply chain management: an empirical study”, International Journal of Physical Distribution & Logistics Management, Vol. 31 No. 4, pp. 247-65.Praest, M. (1998), “Changing technological capabilities in high-tech ﬁrms: a study of the telecommunications industry”, The Journal of High Technology Management Research, Vol. 9 No. 2, pp. 175-93.Prahalad, C.K. and Hamel, G. (1990), “The core competence of the corporation”, Harvard Business Review, Vol. 68, pp. 79-91.Rai, A., Patnayakuni, R. and Seth, N. (2006), “Firm performance impacts of digitally enabled supply chain integration capabilities”, MIS Quarterly, Vol. 30 No. 2, pp. 225-46.Raisinghani, M.S. and Meade, L.L. (2005), “Strategic decisions in supply-chain intelligence using knowledge management: an analytic-network-process framework”, Supply Chain Management: An International Journal, Vol. 10 No. 2, pp. 114-21.
BIJ Rajagopal, P., Zailani, S. and Sulaiman, M. (2009a), “Assessing the effectiveness of supply chain partnering with scalable partnering as a moderator”, International Journal of Physical18,6 Distribution & Logistics Management, Vol. 39 No. 8, pp. 649-68. Rajagopal, P., Zailani, S. and Sulaiman, M. (2009b), “Benchmarking on supply chain partnering effectiveness in two semiconductor companies: a case study approach”, Benchmarking: An International Journal, Vol. 16 No. 5, pp. 671-701.854 Ritchie, B. and Brindley, C. (2007), “Supply chain risk management and performance: a guiding framework for future development”, International Journal of Operations & Production Management, Vol. 27 No. 3, pp. 303-22. ´ Saade, R.G. (2007), “Dimensions of perceived usefulness: toward enhanced assessment”, Decision Sciences Journal of Innovative Education, Vol. 5 No. 2, pp. 289-310. Sambasivan, M. and Jacob, G. (2008), “An empirical study on the impact of supply chain practices on competitive position of MNEs in Malaysia”, International Journal of Economics and Management, Vol. 2 No. 2, pp. 369-94. Sanchez-Rodrıguez, C., Hemsworth, D. and Martınez-Lorente, A.R. (2005), “The effect of supplier development initiatives on purchasing performance: a structural model”, Supply Chain Management: An International Journal, Vol. 10 No. 4, pp. 289-301. Sari, K. (2008), “Inventory inaccuracy and performance of collaborative supply chain practices”, Industrial Management & Data Systems, Vol. 108 No. 4, pp. 495-509. Sezen, B. (2008), “Relative effects of design, integration and information sharing on supply chain performance”, Supply Chain Management: An International Journal, Vol. 13 No. 3, pp. 233-40. Spekman, R.E., Kamauff, J.W. and Myhr, N. (1998), “An empirical investigation into supply chain management: a perspective on partnerships”, Supply Chain Management, Vol. 3 No. 2, pp. 53-67. Tan, K.C. (2001), “A framework of supply chain management literature”, European Journal of Purchasing & Supply Management, Vol. 7, pp. 39-48. Tan, K.C., Handﬁeld, R.B. and Krause, D.R. (1998), “Enhancing the ﬁrm’s performance through quality and supply base management: an empirical study”, International Journal of Production Research, Vol. 36 No. 10, pp. 2813-37. Tan, K.C., Kannan, V.R. and Handﬁeld, R.B. (1998), “Supply chain management: supplier performance and ﬁrm performance”, International Journal of Purchasing & Materials Management, Vol. 34 No. 3, pp. 2-9. Tan, K.C., Kannan, V.R., Handﬁeld, R.B. and Ghosh, S. (1999), “Supply chain management: an empirical study of its impact on performance”, International Journal of Operations & Production Management, Vol. 19 No. 10, pp. 1034-52. Tan, K.C., Lyman, S.B. and Wisner, J.D. (2002), “Supply chain management: a strategic perspective”, International Journal of Operations & Production Management, Vol. 22 No. 6, pp. 614-31. Towill, D.R. (2005), “The impact of business policy on bullwhip induced risk in supply chain management”, International Journal of Physical Distribution & Logistics Management, Vol. 35 No. 8, pp. 555-75. Trkman, P., Stemberger, M.I., Jaklic, J. and Groznik, A. (2007), “Process approach to supply chain integration”, Supply Chain Management: An International Journal, Vol. 12 No. 2, pp. 116-28. Wernerfelt, B. (1995), “The resource-based view of the ﬁrm: ten years after”, Strategic Management Journal, Vol. 16 No. 3, pp. 171-4.
Wisner, J.D. (2003), “A structural equation model of supply chain management strategies and Supply chain ﬁrm performance”, Journal of Business Logistics, Vol. 24 No. 1, pp. 1-25.Wong, A., Tjosvold, D., Wong, W.Y.L. and Liu, C.K. (1999), “Relationships for quality management improvement in the Hong Kong-China supply chain”, International Journal of Quality practices & Reliability Management, Vol. 16 No. 1, pp. 24-41.Wu, F., Yeniyurt, S., Kim, D. and Cavusgil, S.T. (2006), “The impact of information technology on supply chain capabilities and ﬁrm performance: a resource-based view”, 855 Industrial Marketing Management, Vol. 35, pp. 493-504.Yang, B., Yang, Y. and Wijngaard, J. (2007), “Postponement: an inter-organizational perspective”, International Journal of Production Research, Vol. 45 No. 4, pp. 971-88.Yang, B., Yang, Y. and Williams, S. (2010), “Service postponement: translating manufacturing postponement to service operations”, Journal of Manufacturing Technology Management, Vol. 21 No. 4, pp. 470-83.Yeung, J.H.Y., Selen, W., Deming, Z. and Min, Z. (2007), “Postponement strategy from a supply chain perspective: cases from China”, International Journal of Physical Distribution & Logistics Management, Vol. 37 No. 4, pp. 331-56.Zahra, S. and George, G. (2002), “Absorptive capacity: a review, reconceptualization and extension”, Academy of Management Review, Vol. 27 No. 2, pp. 213-40.Zhao, Y. and Simchi-Levi, D. (2002), “The value of information sharing in a two-stage supply chain with production capacity constraints”, Manufacturing & Service Operations Management Decision, Vol. 4 No. 1, pp. 21-4.Zhou, H. and Benton, W.C. (2007), “Supply chain practice and information sharing”, Journal of Operations Management, Vol. 25, pp. 1348-65.Zolait, A.H., Ibrahim, A.R., Chandran, V.G.R. and Pandiyan, V. (2010), “Supply chain integration: an empirical study on manufacturing industry in Malaysia”, Journal of Systems and Information Technology, Vol. 12 No. 3, pp. 210-21.Corresponding authorV.G.R. Chandran Govindaraju can be contacted at: email@example.comTo purchase reprints of this article please e-mail: firstname.lastname@example.orgOr visit our web site for further details: www.emeraldinsight.com/reprints