Exploring relationships among IT-enabled sharing capability, supplychain flexibility, and competitive performance

Yan Jin a,n, Mark Vonderembse b, T.S. Ragu-Nathan b, Joy Turnheim Smith a

a Elizabeth City State University, Elizabeth City, NC 27909, USAb The University of Toledo, OH, USA

a r t i c l e i n f o

Article history:Received 22 October 2012Accepted 21 March 2014Available online 1 April 2014

Keywords:IT-enabled sharing capabilityA manufacturer's supply chain flexibilityExtended resource based view (ERBV)Dynamic view of RBV

a b s t r a c t

This research explores the mechanism through which IT infrastructure enables superior firm perfor-mance by empirically examining the links among IT-enabled sharing capability, supply chain flexibilities(as measured by a manufacturing firm's product development flexibility, production flexibility, logisticsflexibility, suppliers' flexibility, and the flexibility of the supply base), and competitive performance.This study expands the research on IT's impact on competitive performance by focusing on IT-enabledsharing capability and the indirect effect of this capability on firm performance. Most prior researchfocused on the technical aspects of IT infrastructure and tested direct relationships.

In this research, a large-scale survey was used to collect 198 responses from U.S. manufacturers toinvestigate this framework. Structural Equation Modeling was used to examine and test the measure-ment and structural models. The results indicated that IT-enabled sharing capability is associated withflexibilities in a manufacturer's supply chain, which in turn are associated with the firm's competitiveperformance. This finding suggests that a firm should focus on flexibilities in the supply chain to improveits performance. IT-enabled sharing capability is an antecedent for improving these flexibilities.Longitudinal research, multiple respondents, and techniques for improving response rate should beconsidered in future research to provide more robust results.

& 2014 Elsevier B.V. All rights reserved.

1. Introduction

A recent survey of corporate boards of directors by the GartnerGroup found that 52% believe that maintaining competitiveperformance is of extremely high importance (Lopez, 2011). Thesame survey, however, indicated that there is no real consensusabout how that maintenance of competitive performance isrelated to IT capabilities. IT infrastructure itself does not differ-entiate a firm from its competitors because IT applications arebecoming increasing standardized (Zhang and Dhaliwal, 2009).However, greater firm performance and sustainable competitiveperformance can be achieved when IT infrastructure is used tomeet customer-determined organizational needs. IT infrastructurecan create a strong positive impact on the effectiveness of amanufacturing firm's supply chain when it enables the firm'sIT-enabled sharing capability. These sharing capabilities can help

the firm to create unique, difficult to imitate, and non-substitutablecapabilities (Prajogo and Olhager, 2012).

In order to discuss information sharing capabilities, it isimportant to understand what these capabilities entail. Informa-tion sharing capabilities encompass two aspects: (1) the capabilitya firm has of dealing with intangible information that exists withinall of the relevant parts of the firm itself and among suppliers,clients and distribution networks that the firm has, and (2) thefirm's capability of constructing a tangible network to commu-nicate both internally among various areas of the firm andexternally with supply chain members (the integration of the ITsystems to support the connections of information) (Keen, 1991).An example of the first aspect would be the ability of a salespersonto access production scheduling databases and raw materialavailability in order to give a customer an estimated completiondate for a project. An example of the second aspect of theIT-enabled sharing capability would be a system that allowed afirm to see which of its suppliers could best meet price anddelivery needs, which of the firm's production facilities wereavailable for the order and which allowed the firm's customersto access production lead times and status of order production.

While IT-enabled sharing capability adds little to a firm'scompetitive performance without the actual practice of informa-tion sharing, a firm's IT-enabled sharing capability both enhances

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Int. J. Production Economics

http://dx.doi.org/10.1016/j.ijpe.2014.03.0160925-5273/& 2014 Elsevier B.V. All rights reserved.

n Correspondence to: WH223, School of Business and Economics, Elizabeth CityState University, Elizabeth City, NC 27909, USA. Tel.: þ1 252 335 8533;fax: þ1 252 335 3491.

E-mail addresses: yjin@mail.ecsu.edu (Y. Jin),mark.vonderembse@utoledo.edu (M. Vonderembse),traguna@utoledo.edu (T.S. Ragu-Nathan), jtsmirh@mail.ecsu.edu (J.T. Smith).

Int. J. Production Economics 153 (2014) 24–34

the likelihood of the use of that practice and adds value byimproving the level of information processed and the value ofthat information. Within the firm, these sharing capabilities allowan order loaded into the sales system to generate orders for thenecessary raw materials and, upon receipt of expected deliveryinformation facilitated by the external relationships with suppli-ers, to schedule the necessary production time and space, and toreserve space in a delivery vehicle using the appropriate shippingmethod. In order for this model to work, however, informationsharing capabilities must exist that allow the information to passup and down the chain so that the firm can remain in commu-nication with both suppliers and customers. IT-enabled sharingcapability helps to create an information-based platform thatfacilitates flexibility on multiple levels – within the firm, withsuppliers, and in relationships between the manufacturing firmand its suppliers (Lummus et al., 2003). These flexibilities in afirm's supply chain enhance competitive performance, allowingthe firm to meet specific customer needs regarding quality,delivery dependability, and time-to-market better (Gosling et al.,2010; Swafford et al., 2006).

Prior research has generally tested the relationship between ITinfrastructure and firm performance as a direct link, but withinconsistent results. In contrast, this research explores the ideathat this relationship may be indirect, positing that IT-enabledsharing capability may influence the manufacturer's other cap-abilities and help it build competitive performance (Bhatt et al.,2010). With respect to context, prior studies have included bothservice and manufacturing firms. Because there may be a differ-ence in how these firms develop and implement IT infrastructure,including service and manufacturing firms in the same study mayhave confounded the results as well.

In addition, prior studies focused on the technical elements ofIT infrastructure, such as specific applications like EDI that becomeindustry standards, have not supported a link between IT infra-structure and firm performance (e.g., Jeffers, 2010; Peng et al.,2011; Ray et al., 2005). These elements, however, represent thecapacity of IT infrastructure to perform specific functions ratherthan the ability of IT infrastructure to facilitate information sharingand improve decision making. The capacity of IT infrastructuredepends primarily on the decision to invest. It therefore cannot bethe basis for a competitive performance since it is easily copied.

In contrast, the capability of IT infrastructure depends on success-fully infusing IT infrastructure into the organization, which is moredifficult to imitate (Zhang and Dhaliwal, 2009). Thus, althoughcompanies could invest in the same IT infrastructure, the applicationor implementation of IT infrastructure would typically be differentfor different firms, making it the basis for a competitive performance.For example, a proprietary deployment of an IT infrastructure thatfacilitates a manufacturing firm's just in time (JIT) inventory practicesmay add flexibility to the production process by allowing the firm totrack the supplier's work in progress prior to the time of order. Thisinformation would let the firm know if the lead time for a keycomponent is increasing, thus warning the firm that production mayhave to slow down or the component may need to be orderedelsewhere to meet promised delivery schedules. This informationwould also allow the manufacturing firm to choose among suppliers,based on projected delivery times as well as cost. If that process weresimply dependent on hardware compatibility, it would be relativelysimple for a competitor to duplicate the system. In contrast, a systemthat garners information such as that described above must bebased on a culture of openness and collaboration that facilitatesand values communication between a manufacturer and its supplier.Such a culture-supported infrastructure is more difficult to replicate(Fawcett et al., 2011).

This paper addresses the value of the IT-enabled sharingcapability in creating that competitive performance. It contributes

to the IT infrastructure field in three ways. First, it focuses on theIT-enabled sharing capability rather than on the technical aspectsof IT infrastructure. Second, it examines the indirect effect of theIT-enabled sharing capability on firm's competitive performancesvia a firm's supply chain flexibility. Third, it tests these hypothesessampling only the manufacturing industry, thereby avoiding thepotential for an industry confound that may exist when includingother contexts.

2. Theoretical background and research hypotheses

With increasing global competition, manufacturers seek waysto build sustainable competitive performance in order to enhancetheir competitive position. Competitive performance can comefrom a variety of sources, such as differentiation of products andservices based on price, quality or service, but is most sustainablewhen it is difficult to imitate. IT-enabled communication repre-sents one potential source of differentiation. In a firm holding anIT-enabled competitive performance, IT systems ensure timelycommunication both internally and with external suppliers(Akkermans and Horst, 2002; Yang et al., 2009). An example ofsuch a firm would be one where information regarding productionschedules was well communicated internally, allowing for appro-priate staffing and resource utilization, while also being communi-cated clearly with suppliers, ensuring timely deliveries and evaluationof the quality of raw materials.

As shown in Fig. 1, this research examines an element that isvital to the firm's success, IT-enabled sharing capability. Thiscapability represents the extent to which manufacturers canprovide continuous information flows on a well-developed con-nection within the firm and between the firm and its suppliers.IT-enabled sharing capability is directly associated with the flexi-bilities in a manufacturer's supply chain, including elements suchas product development flexibility, production flexibility, logisticsflexibility, suppliers' flexibility, and supply base flexibility. In turnthese supply chain flexibilities are directly associated with thecreation of competitive performances (Gosling et al., 2010). Thus,the relationship between IT-enabled sharing capability and com-petitive performance is linked to the presence of flexibilities in amanufacturer's supply chain.

2.1. The dynamic extension and the relational extension of RBV

As IT infrastructure becomes increasingly uniform, it is moredifficult for manufacturers to acquire unique IT hardware orsoftware that is a scarce heterogeneous resource. For this reason,the dynamic extension and relational extension of the resourcebased view (RBV), not the traditional RBV, provide the propertheoretical lenses to defend the value of IT-enabled sharingcapability in maintaining the manufacturer's competitive position(Bhatt et al., 2010; Byrd and Turner, 2001).

According to the dynamic extension of the RBV, the way a firmuses or exploits its IT infrastructure could vary, thus generating thedynamic organizational capabilities (e.g., IT-enabled sharing cap-ability) that are unique and can create the superior performanceover time (Fawcett et al., 2011). For example, when a manufacturerpurchased a new ERP system, the ERP system per se does notdifferentiate the firm from competitors because it is a commoditythat is readily available for purchase. What makes the difference ishow the firm integrates the individual technology (e.g., RFID) withthe ERP system and how the firm reconfigures the existing process(e.g., order tracking) with the ERP system to synergize actions andresults. This integration and reconfiguration transform unified ITinfrastructure applications (e.g. ERP) into unique capabilities thatfacilitate sharing information and streaming connections within

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–34 25

the firm and between the firm and its suppliers. Thus, they are thestrategic sources of sustainable competitive performance for thefirm (Duncan, 1995; Kayworth, et al., 2001).

The relational extension of the RBV incorporates the relationalview theory, named the extended resource based view (ERBV) byLewis et al. (2010), arguing that the unique capabilities of a firmmay also reside in the relationship with its suppliers (Dyer andSingh, 1998). According to ERBV, a particular IT infrastructure maydevelop sustainable competitive performances by generating arelation-specific capability, which is difficult for competitors tocopy. For example, EDI is an openly available information technol-ogy that connects a firm with its suppliers and facilitates informa-tion sharing with them. Yet, the effectiveness of using EDI largelydepends on the characteristics of the specific buyer–supplierrelationship, such as the level of commitment to use the technol-ogy and the willingness to share information. These long-termoriented characteristics foster specific investment in a particularbuyer–supplier relationship, which in turn improves both infor-mation sharing and the connectivity between manufacturer andsupplier (Fawcett et al., 2011). For example, the relationship couldinclude the ability for the manufacturer to check the supplier'sproduction lead time status before ordering or the use of procure-ment modules that automatically ordered necessary raw materialson receipt of a customer order. A firm's IT-enabled sharingcapability generates the competitive performances over time,because such capability is relation-specific and thereby a uniqueresource.

2.2. IT-enabled sharing capability

Typically, technology by itself is not a rare or heterogeneouslydifferentiated resource. IT-enabled sharing capability, dependingon the way the IT is implemented, however, can be unique anddifficult to imitate (Radhakrishnan et al., 2008). Two aspects ofIT-enabled sharing capability have been used to explain how thefirm can exploit proprietary deployment of IT infrastructure toenhance organization capability effectively.

The first aspect, named IT range, represents the extent to whicha manufacturing firm can provide the seamless information flow inan accurate and timely manner within the firm and with itssuppliers (Bharadwaj, 2000; Closs et al., 2005; Keen, 1991). Thiscompetitive information of a manufacturing firm can be classifiedinto three types – manufacturing information, logistics information,

and strategic information (Fawcett et al., 1996). The ability to accessthis information gives the managers of the firm and its suppliers acomprehensive picture of the situation and helps them makeappropriate decisions (Fawcett et al., 1996). In light of the dynamicextension of the RBV, the ability to provide the needed informationregarding a firm's plans and operations, not the information per se,is a dynamic capability of the manufacturer. Since IT range allows allthree types of this information to flow more smoothly – manufac-turing information flowing through the company from sales topurchasing; logistics from sales to production to shipping; andstrategic information from the firm's policy makers and researchand development to sales and manufacturing, it thus allows thefirm to react more nimbly to changing circumstances. When sharedwith customers and suppliers, it further allows a more seamlesscustomer service experience which may also serve as a competitiveperformance. In addition to the benefits to customer service,knowing more about suppliers – such as knowing their priorperformance, expertise, and capabilities – is of value to the firmsince it helps the firm cooperate effectively with its suppliers. ITrange allows the firm to draw information from a variety of sourcesto create a more complete set of facts on which decisions can bemade, making it relation-specific and therefore particularly valuableas a source of competitive advantage.

The second aspect, named IT reach is the extent to which afirm's IT network connects and supports various functions atdifferent levels within the firm, connects the firm with itssuppliers and supports the relationship between the firm andits suppliers (Bharadwaj, 2000; Closs et al., 2005; Keen, 1991).It does not necessarily reflect the raw number of functions con-nected and supported by IT infrastructure; rather it reflects thevalue of these functions in improving the performance of the firmand the supply chain. An IT network provides a shared foundationthat allows a firm to assess, link, exchange, and disseminateavailable information as needed. Physical IT network hardware(e.g., computers) by themselves do not give distinctive advantagesto a firm, because that hardware can be easily purchased on theopen market. Likewise, in most cases, the IT software is also readilyavailable for purchase and installation. However, as suggested bythe dynamic and relational extensions of the RBV, integratingindividual hardware and software components and making themwork cooperatively requires time, effort, understanding and com-mitment. Such integration is not easily duplicated by a competitor.Thus IT reach may help a firm achieve improved competitive

Research Model

00

Suppliers’ flexibility

Production Flex

Supply chain flexibility

H3

H1

Product Dev. Flex

Supply base flexibility

H2

Logistics Flex

Competitive advantage

CA1

CA2

CA3

Annual Sales

Industry Sector

IT-enabled sharing

capability

ITSC2

ITSC3

ITSC4

ITSC6

Fig. 1. The research model.

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–3426

performance through a sustainable competitive advantage(Bharadwaj, 2000).

In addition, the two aspects of IT infrastructure capabilityinfluence each other. An integrated IT network enhances transpar-ency within the firm and within the firm's supply chain, so thatthe manufacturer can promptly detect variations in its operationsas well as in suppliers' changes in production and delivery. As aresult, such a network provides the foundation for having accurateand timely information. In return, information about the firm'soperation and suppliers' performance reinforces the value of theintegrated network garnered by both parties. Seamless informa-tion flow brings the latest updates regarding the manufacturer andits suppliers to the attention of management of the relevantentities. Based on this information, the manufacturer can makeany adjustments necessary to align the actions of the supply chainwith changing demand.

2.3. Flexibilities in supply chain

Flexibilities in a firm's supply chain serve as an intermediatingvariable that links IT-enabled sharing capability to a firm's com-petitive performance. Flexibility is increasingly important inaccommodating uncertainty in the business environment (Kosteand Malhotra, 1999; Narasimhan et al., 2004). From the 1980s tothe early 2000s, flexibility research focused on how a firm'sflexible manufacturing and product development capabilitiescould respond to environmental uncertainty and could enhancefirm performance (Koste and Malhotra, 1999; Narasimhan et al.,2004; Stevenson and Spring, 2007). With the emergence of supplychain management in the late 1990s, flexibility research expandedto include a firm's supply chain components (e.g., logistics flex-ibility) and later to include suppliers' flexibility and the supplybase flexibility (Swafford et al., 2006). Based on Lummus et al.(2003)'s conceptual model, these flexibility variables are discussedas follows.

A manufacturing firm's flexibility, in a dynamic supply chain, isimportant to successfully sustaining the firm's competitive posi-tions and long-term profitability (Stevenson and Spring, 2007).A manufacturing firm's flexibility is the firm's ability to adjustits product development, logistics, and production processesefficiently and effectively, so it can adapt to changes in theenvironments, in particular changes in final customer demand(Narasimhan et al., 2004). Flexibilities in product development andproduction represent the capabilities of a manufacturer's manage-ment regarding new products and production processes (Kosteand Malhotra, 1999; Zhang et al., 2003). Logistics flexibility reflectsthe abilities of the firm's procurement system to accommodatevarious receipt and delivery requests accurately, quickly, andefficiently (Prater et al., 2001). Product development, logistics,and production are highly interrelated functions within the firm(Prater et al., 2001). For example, production and logistics providea foundation to support product development. Without such afoundation, the competitive performances generated by innova-tive products and by substantial modifications to existing productswill diminish quickly (Teece, 1986).

With the growing pressure on supply chains to respond quicklyand efficiently, the flexibility of each supply chain member, such assuppliers' flexibility, rather than the manufacturer's flexibility aloneis important (Lau, 1999; Swafford et al., 2006). In the currentenvironment, where the level of vertical integration is limited, it isdifficult to imagine that a firm could accommodate customerdemand for product variety without the assistance of flexiblesuppliers (Das and Abdel-Malek, 2003). Suppliers' flexibility is theability of vendors to efficiently and effectively adjust their opera-tions to cope with a manufacturer's requests for components

needed to meet the final customers' demands (Das and Abdel-Malek, 2003; Pujawan, 2004). This flexibility has positive impactson a manufacturer's product development, production, logistics,and other capabilities (Lau, 1999). To a manufacturer, the mostimportant elements of suppliers' flexibility are order quantity andproduct variety, which determine its ability to provide the rightamount and the right type of products in a timely manner(Tachizawa and Thomsen, 2007). Because a manufacturer is striv-ing to satisfy its customers on multiple competitive dimensionssimultaneously, it views suppliers' flexibility as a way of integrat-ing both its needs and those of the customers.

Supply base flexibility is a firm's ability to change its buyer–supplier linkage without high penalties (cost, time, and effort)(Gosain et al., 2004; Lummus et al., 2003). Supply base flexibilityresides in the connection between the manufacturing firm andsupplier firms, not within these firms, as is the case with both amanufacturing firm's flexibility and suppliers' flexibility. Thisflexibility is important because supply chain performance dependson the performance of each supply chain member and theeffectiveness of the connections among the members. Consider-ing the different ways of varying a buyer–supplier relationship(e.g., adding a new supplier, changing the closeness of therelationship, switching purchasing orders to an alternative sup-plier), two focuses of flexibility (i.e., range and mobility) stand out(Pujawan, 2004; Stevenson and Spring, 2007). First, the range ofsupply base flexibility indicates the number of qualified suppliers.When emergencies arise, the availability of qualified suppliers towhich orders can be switched is critical in maintaining theexpected manufacturing schedule. For example, the 2011 tsunamiin Japan and flooding in Thailand caused severe disruption forsome auto companies with key suppliers in those countries andrelatively few alternatives in other countries (Powell, 2011).Second, mobility or responsiveness represents the manufacturer'sefficiency in developing new suppliers, adjusting supplier relation-ships, and switching purchasing orders. When rapid adjustmentsare made at low cost, the competitive position of the supply chainis maintained.

Suppliers' flexibility and supply base flexibility correlate witheach other and are associated to the firm's flexibility. These twotypes of flexibilities are an asset specific to the manufacturing firm,which both adds value to the supplier–manufacturer relationship(Dyer and Singh, 1998) and is imperfectly imitable and imperfectlysuitable as well as rare (Lavie, 2006). A manufacturer with a highsupply base flexibility (e.g., a strong ability to identify a newsupplier or make a quick transition if necessary) can determine thebest source to use to meet customer demand, even if that meansusing a different supplier than would normally be used (Gosainet al., 2004; Gosling et al., 2010). When a firm has a broad supplybase, it can use that base to respond to last-minute needs fromdifferent quantities of supplies or different supplies altogetherwithout having any adverse effect on the performance of thesupply chain. This ability gives the firm a high level of suppliers'flexibility. IT-enabled sharing capability facilitates supply baseflexibility and suppliers' flexibility by enhancing the depth ofinformation shared. This depth of information reflects the partner-ship nature of the relationship rather than merely the presence ofthe supplier in the network. Further, the dynamic adaptabilitycreated by these partnerships creates a high level of flexibility forthe manufacturer that helps it respond to various customers'demands. For these reasons, a manufacturing firm's supply chainflexibility is a higher order construct that includes product develop-ment flexibility, production flexibility, logistics flexibility, suppliers'flexibility, and supply base flexibility (Mishra and Shah, 2009).

IT-enabled sharing capability influences all these flexibilities.First, IT-enabled sharing capability influences the firm's flexibility

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–34 27

by (1) keeping the manufacturing firm updated with accurate andtimely information and (2) building the capability of collecting,analyzing and disseminating information within the firm and withsuppliers in an efficient and effective way. Being able to continu-ously monitor its own operations and supply chain operationsallows the manufacturer to detect changes in the environment andrespond quickly by adjusting its actions (e.g., product design,production, and logistics) (Fawcett et al., 1996). In addition, betterIT-enabled sharing capability also lowers the cost and reduces thetime needed for refining and reengineering the business process(Duncan, 1995). As a result, the manufacturing firm will be able toadjust its supply chain operations flexibly in response to thechange in customer demand.

Besides the influences on the firm's flexibility, IT-enabledsharing capability also influences the flexibility of the firm'ssuppliers and its supply base. Built on a connected platform,well-integrated IT infrastructure and inter-organizational activities(such as order release, tracking and expediting) enable a high levelof timely and accurate information exchange with its suppliers.When shared through the network, information regarding down-stream activities, such as product demand, the production process,and distribution, can dramatically reduce the impact of uncer-tainty for upstream suppliers (Fawcett et al., 2011; Field and Meile,2008). Being aware of what has happened in the manufacturer'ssupply chain enables suppliers to be able to adjust their operationsand to be aligned better with the manufacturer's request, which isa higher flexibility for suppliers. In addition, the manufacturer,through its information sharing capabilities, will be able to accessinformation about the changes happening on a supplier site, suchas a production interruption. Should such an interruption occur,the firm can look for a substitute supplier if needed by tappinginto its network of alternate suppliers (i.e. using its higher level ofsupply base flexibility). In addition, the IT-enabled sharing cap-ability enables the firm to know both the existing suppliers andthe potential qualified suppliers better, which makes the manu-facturer efficient and effective in developing a new buyer–supplierrelationship or in strengthening the existing relationship (i.e. higherlevel of supply base flexibility).

Therefore, it is hypothesized that IT-enabled sharing capabilityhas a direct positive relationship with the flexibilities in amanufacturing firm's supply chain (Hypothesis 1).

2.4. Competitive performance

Competitive performance is used as a proxy for the desiredaccounting measures, innovation performance, product performanceand sales performance (Shan and Jolly, 2010). Competitive perfor-mance refers to the outcome of competitive advantage, whichindicates the extent to which an organization is able to develop anedge over its competitors (McGinnis and Vallopra, 1999). Variousmeasures such as cost, time, and quality have been discussed in priorflexibility and IT-related literature. In this study, quality, dependabledelivery, and time-to-market are considered. Cost is not includedbecause cost and the other three measures represent two distinct setsof measures (Krause et al., 2007). In this research, quality means tocompete by having products that consistently meet or exceed thecustomer's expectations. Dependable delivery means to compete byconsistently delivering the right product to customers at the righttime. Time-to-market means to compete by providing the innovativeproducts faster to customers. These competitive advantages reflect themanufacturer's ability to provide a high level of customer serviceresulting in a competitive performance (Shepherd and Gunter, 2005),which cannot be easily copied by other competitors and thus havesustainable value.

A manufacturing firm's supply chain flexibility affects itscompetitive performance in three ways. First, a manufacturer's

supply chain flexibility indicates the ability to maintain a highlevel of performance across all facets and all changes in itsoperations and in its supply base. This enables the manufacturerto offer products with high quality and achieve the qualitycompetitive performance. Second, supply chain flexibility showsthe manufacturer's ability to work with suppliers to provide awide variation of products, very different production outputs, andvarious deliveries, which gives the firm the ability to deliver theright product to customers at the right time and achieve thedependable delivery competitive performance. Third, a manufac-turing firm with high supply chain flexibility means that the firm,with the help from their flexible suppliers and the flexible supplybase, can quickly and cost-effectively introduce different newproducts, modify existing products, adjust output volumes andproduct mixes, and change logistics systems. As a result, the firmwill be able to offer products with a swift response and achievethe time-to-market competitive performance.

In some literature discussing a firm's competitive performance(e.g., the cumulative capabilities), a firm's flexibility is the part of thecapabilities that also includes quality and delivery, where quality is thefoundation to achieve delivery and flexibility (Grobler and Grubner,2006). We propose the relationship in a different direction for thefollowing reason. The flexibility, quality and delivery referred to in thecumulative capabilities are a firm's internal manufacturing capabilities,such as volume flexibility, mix flexibility, and manufacturing confor-mance. In contrast, this research looks at the supply chain flexibility ashaving both an internal flexibility component that can lead to productinnovation (e.g., product development flexibility) and a componentinvolving interactions with suppliers which supports product innova-tion (e.g., logistics flexibility and supplier base flexibility, suppliers'flexibility). We take this perspective because we believe that innova-tion is one of the key elements of competitive advantage along withdependability and quality.

It is hypothesized that a manufacturing firm's supply chainflexibility has a direct positive relationship with the firm's com-petitive performance (Hypothesis 2).

In this research, IT-enabled sharing capability can be viewed as theinternal ability a manufacturing firm has to exploit their integratedinformation systems to share the information within the firm andbetween the firm and its suppliers. ITSC is directly important to andsupportive of a manufacturer's supply chain flexibility, while ITSC'sdevelopment may indirectly help achieve other capabilities as well.Supply chain flexibility is less visible than the visible elements ofcompetitive performance that are seen by customers (e.g., quality,dependable delivery and introduction time of new products). A manu-facturing firm's flexibilities (i.e. product development flexibility,production flexibility and logistics flexibility) and suppliers' flexibilitydepend on the manufacturing firm's IT-enabled sharing capabilityallowing it to gather information regarding customer interests andsupplier modifications. This IT-enabled sharing capability must furtherallow the efficient and effective change of the supplier–manufacturerconnection (i.e. the flexibility of supply base) as a means of expandingthe variety of offerings or permutations of offerings by the manu-facturing firm.

It is hypothesized that IT-enabled sharing capability has anindirect positive relationship with a manufacturing firm's com-petitive performance through the firm's supply chain flexibility(Hypothesis 3).

3. Research design and methodology

3.1. Measurement development

Items of IT-enabled sharing capability were developed basedon information technology literature (Bharadwaj, 2000; Closs et al.,

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–3428

2005; Fawcett et al., 1996; Keen, 1991; Li, 2006; Li et al., 2005; Zhanget al., 2006). Keen (1991) discusses IT infrastructure in terms of ITreach and IT range and their impact on competitive advantage. Closset al. (2005) suggest that there are two elements that are of criticalinterest here – timeliness and sharing between the firm and itssupplier. Fawcett et al. (1996) suggest that two major categorizations –manufacturing information and logistics information. Li et al. (2005)suggests the importance of accuracy and timely information. Thesereferences translated into the inclusion of the first three ITSC items.Li (2006) and Zhang et al. (2006) indicate the importance of theconnection of relevant parts in the manufacturing firm suggestingitems regarding the use of the IT system in a way that supportscompetitive advantage for the firm.

All five flexibility variables were developed based on twopopular aspects of flexibility, range and mobility/adaptability(e.g., Koste and Malhotra, 1999; Swafford et al., 2006). Rangerepresents the number of states an organization can adopt;mobility is the ease of changing from one state to another interms of cost and time. From these two aspects, each flexibilityvariable was developed from various flexibility literatures. Theitems measuring product development flexibility came fromexisting literature, which discussed the ability for new productintroduction and design change accommodation (e.g., Narasimhanet al., 2004; Vickery et al., 1999). Production flexibility items werebuilt on the literature of volume and mix flexibilities (e.g.,Swafford et al., 2006; Zhang et al., 2003). Logistics flexibility itemscame from the concept of Zhang et al. (2002)'s physical supply andpurchasing flexibilities, with an emphasis on the ability of a firm'sinbound transportation to provide the needed materials andsuppliers. Suppliers' flexibility measures were based on Lau(1999)'s analysis of a supplier's ability to change productionvolume and variety. Supplier base flexibility items were extendedfrom Gosain et al. (2004)'s partnering flexibility regarding the easeof replacing the existing supplier with a new supplier. We addedtwo items to reflect the different ways of changing a manufac-turer's supply base.

Items focusing on the firm's competitive advantage, the poten-tial to achieve the competitive performance, were modified fromperformance measures used in prior research (e.g., Krause et al.,2007). All variables were measured through managerial percep-tions by using 5-point Likert scales (1¼strongly disagree to5¼strongly agree).

Two most commonly used control variables, a firm's industrysector (SIC code) and the number of employees, are used in theresearch model. First, SIC codes are recoded as nine dummyvariables (SIC20, SIC25, SIC28, SIC30, SIC34, SIC35, SIC36, SIC37,and SIC38) to classify the sample into 10 groups according to amanufacturing firm's industry sector. Second, the number ofemployees is recoded as three binary variables (EMP_1 for firmsunder 100 employees; EMP_2 for firms with 100–249 employees;and EMP_3 for firms with 250–999 employees) so that manufac-turing firms in this research were grouped into four categoriesaccording to the firm size. These variables are included to controlthe effects of industry sector and firm size on competitiveadvantage so that the research model is a complete model andresults are rigorous.

A questionnaire was developed after conducting a carefulliterature review of IT infrastructure, supply chain flexibility, andfirm performance to ensure the initial content validity of instru-ments (Haynes et al., 1995). The questionnaire was pre-tested torefine the content validity through consultation with professionalsand practitioners who have extensive knowledge in this field.A Q-sort method was applied in a pilot study to assess the pre-liminary convergent validity and discriminant validity of theinstruments (Moore and Benbasat, 1991). Items were revised asneeded and the final version is given in Appendix A.

3.2. Data collection

The data was collected from an online survey which took placefrom September to December 2007. The study population includedsupply chain professionals in various U.S. manufacturing compa-nies. An initial invitation was sent to each of the potentialrespondents by email with a link to the online survey website.Two reminder emails were sent out afterwards. Respondents wereoffered the research results as an incentive for participation andprovided with other options (e.g., mail or fax) for them to answerthe survey. Finally, 198 usable responses were received from a poolof 6485, after excluding 1424 undeliverable email addresses. Theresponse rate (3.3%) of this research was comparable to recentresearch in management literature (e.g., Beltran-Martin et al.,2008), considering a large amount of emails were likely filteredby security systems, a large number of emails were idle because ofrelocation, and the response level of top managers continues todecline (Baruch, 1999; Klassen and Jacobs, 2001).

Next, the external validity of the sample was examined basedon the sampling design, its representativeness, and sample size(Short et al., 2002). First, the study population was collected fromthree databases of executive contacts: RSA Teleservices, Lead411,and the Council of Supply Chain Management Professionals(CSCMPs), all three accounting for a large share of the totalbusiness and total population of U.S. firms. In addition, the samplecovered more than nine manufacturing sectors with a goodbalance (Table 1). The sample also covered manufacturing firmsin different sizes (58% with more than 1000 employees, 29% with100–1000 employees, and 22% with fewer than 100 employees)and different annual sales (54% with over $500 M, 36% with$10–500 M, and 8% with less than $10 M). For these reasons, theresults could be generalized for small, medium, and large firmsacross a variety of manufacturing industries. Moreover, respon-dents (top executives – 42%, senior production managers – 15%,senior logistics managers – 16%, senior purchasing managers –

21%) would have knowledge of the capabilities of their companiesand suppliers, which is suitable for this research.

Second, the sample represented the population in terms of firmsize and annual sales, both frequently used in accessing the non-response bias. Differences between the 198 respondents and thepopulation1 were examined by using chi-squared tests (Shortet al., 2002) among four categories (under 100, 100–249, 250–999, and more than 1000) for firm size and five categories (under

Table 1Profile of respondents.

Frequency Percentage (%)

Industries (SIC code)Electronic/electrical equipment (36) 60 30.30Industrial/commercial machinery (35) 30 15.15Instruments and related products (38) 25 12.63Chemicals (28) 20 10.10Transportation equipment (37) 16 8.08Furniture and fixtures (25) 11 5.56Rubber and plastic products (30) 9 4.54Fabricated metal products (34) 9 4.54Food (20) 7 3.54Others (39) 11 5.56

Total 198 100.00

1 One source that provided a mailing list did not disclose information aboutcompany size and annual sales. The number of contacts provided by this source isless than 15% of the entire population. Therefore, we calculated the non-respondentbias by comparing the respondents with the population from the other two sourceswhere the company size and annual sales information were available.

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–34 29

$10 M, $10–49 M, $50–99.9 M, $100–499.9 M, and more than$500 M) for annual sales. The results (χ2¼2.98, df¼3, p40.25for firm size, and χ2¼1.87, df¼4, p40.5 for annual sales) indicatedno significant differences between the sample and the population;thus, response bias is not an issue. Third, a sample size over 150 or200 is commonly considered necessary to be able to perform astable and a rigorous SEM model (Hair et al., 2005), and thesample size of 198 useable respondents met this need.

4. Measurement model results and structural model fits

4.1. Common method variance

Because the survey was answered by a single informant,common method variance was checked before conducting furthervalidations (Podsakoff et al., 2003). Common method varianceexists if a measurement model that includes all items shows agood model fit. The common model-fit indexes were calculated tojudge the validity of this measurement model. Because no indexwas close to the acceptable value (Byrne, 2001) (χ2¼1124.990,df¼190; RMR¼0.155; NFI¼0.472, CFI¼0.513; RMSEA¼0.158, 90%CI: 0.149–0.167), common method variance was unlikely to beproblematic.

4.2. Measurement model results

A manufacturing firm's supply chain flexibility (SCF) wasmeasured by five first-order variables (i.e., product developmentflexibility – PDF, production flexibility – PF, logistics flexibility – LF,suppliers' flexibility – SF, and supply base flexibility – SBF). TheIT-enabled sharing capability (ITSC) and the competitive advan-tage (CA) were first-order variables. Confirmatory factor analyses(CFA) were used to examine the unidimensionality and reliabilityof seven first-order variables and one second-order variable. Thefit indexes of the measurement model (including all variables inTable 2) indicate the model is acceptable (χ2¼271.299, df¼181;RMR¼0.059; NFI¼0.873, CFI¼0.953; RMSEA¼0.050, 90% CI:0.037–0.062).

Table 2 shows descriptive statistics, factor loadings, criticalratio and R2 from CFA. All item-to-factor loadings were greaterthan 0.5 (po0.001), indicating the acceptable scale unidimension-ality (Ellis et al., 2010; Shah & Goldstein, 2006). Table 3 showsCronbach's alpha, average variance extracted (AVE), compositereliability (CR), and the maximum shared variance (MSV), andthe average shared variance (ASV) for all scales. CR valuesexceeded 0.7 cutoff for all variables, indicating the acceptablereliability (Fornell and Larcker, 1981). AVE values of all variablesexcept CA and SCF surpassed the 0.5 cutoff. The AVEs of CA andSCF were actually very close to the cutoff values. CR of eachvariable is greater than its AVE, indicating that the convergentvalidity is satisfied (Fornell and Larcker, 1981).

The discriminant validity was assessed by comparing the AVEand the MSV for each variable (Fornell and Larcker, 1981). The MSVfor each variable was less than the AVE for that variable (Table 4),which indicated the adequate discriminant validity for all variables(Fornell and Larcker, 1981). The only exception is SCF and CA,which MSV is close to but greater than its AVE. This MSV is thesquared value of the correlation between SCF and CA. Discriminantvalidity for SCF and CA is then evaluated by the difference in thevariances (χ2 values, df¼1) of a correlated model of these twovariables and a single factor model consisting of all items of twovariables. Δχ2 (20.8) is significant at po0.001 level, supportingthe discriminant validity between SCF and CA (Anderson andGerbing, 1988).

Since SCF is a second-order factor, a target-coefficient (T) wasused to validate the existence of this higher order structure (Marshand Hocevar, 1985). T is a ratio of the chi-square of the first-ordermodel (correlating all five first-order flexibilities, PF, PDF, LF, SF,and SBF) to the chi-square of the second-order model (loading allfive first-order flexibilities PF, PDF, LF, SF, and SBF onto the second-order factor SCF). T value was 0.93, indicating that the majorvariance among PF, PDF, LF, SF, and SBF was captured by the higher

Table 2Descriptive statistic, factor loadings, critical ratio, and R2 from CFA.

Item Mean S.D Factor loading Critical ratio R2

IT-enabled Sharing Capability (ITSC)ISC1a 3.687 0.957 – – –

ISC2 3.444 1.068 0.701 9.898 0.492ISC3 2.909 1.172 0.790 11.174 0.625ISC4 3.444 1.083 0.664 9.308 0.441ISC5a 3.338 1.197 – – –

ISC6b 3.116 1.193 0.828 – 0.686

Competitive Advantage(CA)CA1b 4.525 0.674 0.703 – 0.494CA2 4.222 0.873 0.781 8.228 0.610CA3 3.778 1.062 0.584 6.854 0.341

Product Development Flexibility (PDF)PDF1a 3.864 1.050 – – –

PDF2b 3.525 1.001 0.747 – 0.559PDF3 4.030 0.842 0.681 8.977 0.464PDF4 3.768 0.965 0.869 10.604 0.755

Production Flexibility (PF)PF1b 3.687 0.984 0.803 – 0.645PF2 3.631 1.023 0.890 13.044 0.793PF3a 3.975 0.920 – – –

PF4 3.742 0.878 0.751 11.108 0.564

Logistics Flexibility (LF)LF1b 3.859 0.7999 0.882 – 0.777LF2 3.576 0.952 0.848 11.322 0.720

Supply Base Flexibility (SBF)SBF1b 3.717 1.023 0.745 – 0.554SBF2 3.672 1.002 0.847 11.000 0.718SBF3 3.419 1.104 0.836 10.935 0.699

Suppliers' Flexibility (SF)SF1b 3.626 0.879 0.814 – 0.663SF2 3.621 0.845 0.821 10.186 0.675SF3a 3.737 0.826 – – –

SF4 3.581 0.838 0.631 8.426 0.398

Supply Chain Flexibility (SCF)PDF 3.604 0.693 0.745 5.619 0.555PF 3.598 0.744 0.792 5.959 0.627LF 3.428 0.658 0.742 5.930 0.550SF 3.528 0.655 0.605 5.203 0.366SBFb 3.093 0.709 0.583 – 0.340

a Deleted item after purification in CFA.b Items with the regression weights of 1 in CFA.

Table 3Descriptive statistic, Cronbach's alpha, CR, AVE, MSV, and ASV.

Mean S.D. Cronbach'salpha

CR AVE Maximumshared variance

Averagesharedvariance

ITSC 3.440 0.913 0.837 0.846 0.561 0.274 0.144CA 2.857 0.421 0.690 0.733 0.482 0.555 0.268PDF 3.604 0.693 0.751 0.812 0.592 0.467 0.248PF 3.598 0.744 0.855 0.857 0.667 0.466 0.275LF 3.428 0.658 0.848 0.856 0.749 0.250 0.181SF 3.528 0.655 0.796 0.802 0.578 0.316 0.242SBF 3.093 0.709 0.848 0.851 0.657 0.247 0.172SCF 2.657 0.405 0.858 0.824 0.488 0.555 0.407

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–3430

order construct SCF (Segars and Grover, 1998). Therefore, thesecond-order structure of SCF was justified.

4.3. Structural model fits and results of hypotheses

After constructs were validated, the hypothesized relationshipswere tested in a structural model. The weighted scores werecalculated for PF, PDF, LF, SF and SBF. The composite scores wereused as the observed items for a manufacturing firm's SCF in thestructural model. ITSC and CA were first-order variables andcorresponding items were observed items for those variables inthe structural model. The results (Table 4) of the structural modelindicated a reasonable model fit (χ2¼296.991, df¼171; RMR¼0.044; CFI¼0.937, NFI¼0.870; RMSEA¼0.061, 90% CI: 0.049–0.073). All hypotheses were supported.

Hypothesis 1. showed that IT-enabled sharing capability is posi-tively associated with a firm's supply chain flexibilities (t¼4.802and standardized coefficient¼0.403). ITSC reflects a manufactur-ing firm's ability to integrate different processes and streamlineinformation exchange across the different business functions andwith the supply chain firms. According to the dynamic extensionof RBV, developing ITSC is a process that transforms the manu-facturing firm, and as such is unique and difficult for competitorsto imitate. Such a dynamic capability helps the manufacturing firmknow what to do at what time, which makes them more flexible.In addition, shared information based on the integrated IT pro-cesses between the manufacturing firm and suppliers keeps theupstream suppliers updated about the downstream activities inthe supply chain and allow supply chain members to communicatemore frequently and smoothly. Possessing the relation-specificinformation may allow the suppliers to respond to the manufac-turer's request quickly. Thirdly, in order to keep suppliers withhigh flexibility in the supply base over a long period of time, themanufacturing firm needs to be able to select and change thesupplier as needed. For example, if the manufacturer was able toconnect to the potential flexible suppliers, the manufacturing firmcould use that flexibility to identify and switch to a different, moreappropriate supplier quickly.

Hypothesis 2. showed that a manufacturing firm's supply chainflexibility is positively related to the firm's competitive perfor-mance (t¼7.018 and standardized coefficient¼0.805). When amanufacturing firm is flexible to customer requests with the helpfrom flexible suppliers and the flexibility to change the supplybase, the firm is able to provide different options, to change fromone option to another efficiently and effectively, and to maintainconsistent performance regardless of the option chosen. Withthese competences, the manufacturing firm will be able tocompete with other companies on quality, dependable delivery,and time-to-market of product introduction, which all indicate ahigher potential to have enhanced competitive performance.

In order to test whether the effect of a manufacturing firm'ssupply chain flexibility has a mediating effect or an indirect effecton the ITSC–CA relationship, two structural models were testedaccording to the procedure suggested by Baron and Kenny (1986)and Holmbeck (1997). The first model is a direct effect model withonly ITSC and CA. The second model is a mediated model includingSCF as an intermediate variable. In the direct effect model, ITSCshowed an insignificant association with CA (t¼1.221 and stan-dardized coefficient¼0.438). Because of this insignificant relation-ship, the effect of SCF on the ITSC–CA relationship can only be anindirect effect, but not a mediated effect. We continued to test theeffect of SCF in the mediated model. The association of ITSC and CAis insignificant in the mediated model (t¼�0.411 and standar-dized coefficient¼�0.107) and H1 and H2 are both significant.

In addition, results showed that the direct effect between ITSCand CA is insignificant at p¼0.705 (estimates¼�0.107) and theindirect effect is significant at p¼0.002 (estimates¼0.325). There-fore, ITSC is associated with CA indirectly through SCF but notmediated by SCF, and thus hypothesis 3 is supported.

5. Discussion, conclusions and implications

Today, under pressure to sell more for less, manufacturers arestruggling to improve flexibility that is needed to achieve compe-titive performances in customer service. Because competitionexists not only at the firm level but also at the supply chain level,the effectiveness of its suppliers including how they utilizeresources is essential for a firm to differentiate its performancefrom its competitors (Fawcett et al., 2011). The dynamic andrelational extensions of RBV both indicated that the possessionof IT resources is not as important as the firm-specific or relation-specific capabilities that can be generated from these resources.This research shows that sharing capability enabled from IT, i.e.,firm-specific and relation-specific capability, has a direct impacton the firm's supply chain flexibility, which includes a firm'sproduct development, production and logistics, suppliers' andsupply base flexibilities. In turn, the firm's supply chain flexibilityinfluences the firm's competitive advantage and ultimately thefirm's competitive performance. Thus a firm with a wide networkof suppliers that has sophisticated data interfaces that allow forreal-time calculation of shipping time, work in process status andmodification deadlines is better able to sustain a competitiveperformance in customer service than a firm with fewer supplieroptions and less information.

While prior research testing the direct relationship between ITinfrastructure and firm performance presented contradictoryresults, this research contributes to the IT literature by presentingan empirical path that may explain these conflicts by linking theIT-enabled sharing capability to the firm's competitivenessthrough flexibility. As shown in the direct model, IT-enabledsharing capability has no direct association with competitiveadvantage, which means that if a manufacturing firm with ITSCcannot end up with a more flexible supply chain, the firm'scompetitive performance would not be improved. Because theflexible supply chain makes a manufacturing firm to be competi-tive in meeting customers' demand, a firm's CA is improved only ifa manufacturing firm supply chain (itself, its suppliers and itssupply base) responds flexibly to customers' requests (Hypothesis 2)with the help from a well-integrated information system anda streamlined information sharing process (Hypothesis 1). Thedirect/indirect effects ITSC on CA in the mediated model alsoconfirm the indirect effect of supply chain flexibility on theITSC–CA relationship.

Another contribution of this research is to emphasize informa-tion sharing capacity rather than focusing on the technicalperspective of IT infrastructure. The IT-enabled sharing capabilitymay make the firm's competitive performances sustainablebecause it is dynamic and is not easily copied by competitors.Thus, results of this research also reveal important practitionerimplications for IT-enabled sharing capability. The firm shouldinvest in practices that enhance the IT-enabled sharing capability,such as employee training to improve the effectiveness of using ITapplications or more communication approaches with suppliers tofoster an information sharing culture. These practices will improvethe information flow and advance the integration across differentdepartments within the manufacturing firm and among supplychain members. The enhanced IT-enabled sharing capabilitymakes it easier for the manufacturer to trace the material flowin its supply chain (Fantazy et al., 2009). These improvements

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–34 31

enable the firm to build flexibility and achieve multiple competi-tive objectives and as such both improve the bottom line for thecorporation. Such competency will bring more profits for the firm.

5.1. Limitations and future research

Although this research provides several significant contributions,some limitations need to be addressed in future research. First, thisresearch is a cross-sectional study. Future longitudinal research mayprovide further insights underlying relationships between IT-enabled sharing capability, supply chain flexibility, and competitiveperformance. Second, multiple respondents, multiple methods forobtaining measures and randomizing the order of items can be usedin future research to moderate the mono-respondent problem.Third, future research might attempt to improve the response rateby using different media for data collection, reaching the intendedrespondents via state-of-the-art techniques, shortening the ques-tionnaire, and establishing collaborative relationships betweenresearchers and respondents (Dillman et al., 2009). Fourth, becauseof the low reliability of competitive performance, a second-orderconstruct might be considered to better represent this variable. Inaddition, the perceptual measures of business performance could beadded in the survey to test how IT-enabled sharing capabilities,supply chain flexibilities, and other cumulative capabilities willinfluence the manufacturing firm's performance. Moreover,although the model fits are acceptable, they were not great. Thismight be the result of some double-barreled items for IT-enabledsharing capability. For example, “Our IT system provides accurateand timely information” can be broken up into two items “Our ITsystem provides accurate information” and “Our IT system providestimely information”. Balanced items between the internal and theexternal measures for IT-enabled sharing capability are recom-mended as well.

In addition to these methodological limitations, differentresearch models can be considered. Human skills are discussedwidely in IT infrastructure management (Ray et al., 2005). Peopledecide what information technology to use and how to use it.Employee knowledge and ability constrains the IT-enabled sharingcapability. Examining the interdependence between humancapital and information technology and the effect of their inter-actions on the firm's supply chain flexibility and competitive

performances therefore may also be a fruitful area of research. Inaddition, cost is an important competitive advantage (Sarmientoet al., 2010). It is a good idea to test the influences of IT-enabledsharing capability and flexibilities in the supply chain on costleadership in future research. Porter's cost vs. quality as sources ofcompetitive advantage and eventually competitive performance(e.g., financial performance) can also be included in the futuremodel (Porter, 1985).

Overall, the implications of IT infrastructure to create IT-enabledsharing capability suggest that the key to competitive performancethrough IT is not reflected solely in network complexity or theacquisition of cutting edge technology, but rather how firms use whatthey have and exploit the advantages generated from partner relation-ships with both suppliers and customers.

Appendix A. List of items in survey questionnaire

IT-enabled Sharing Capability (ITSC)ITSC1: Our IT system provides accurate and timely informationfor manufacturing operationn

ITSC2: Our IT system provides accurate and timely informationfor logistics operation

ITSC3: Our IT system provides accurate and timely informationfor our suppliers' performances

ITSC4: Our IT system aligns different internal functionsITSC5: Our IT system supports joint production planning andscheduling among purchasing, manufacturing, marketing,and distributionn

ITSC6: Our IT system supports the management of linkagesbetween our firm and our suppliers

Manufacturing Firm's Supply Chain Flexibility (SCF)Product Development Flexibility (PDF)PDF1: Our firm can introduce many different new productsn

PDF2: Our firm can introduce new products efficientlyPDF3: Our firm can implement many different productmodificationsPDF4: Our firm can implement product modificationsefficiently

Table 4Summary of hypotheses testing.

Mediated model Direct effect model

AMOS coefficient t-value AMOS coefficient t-value

ITSC-SCF 0.403 4.802a – –

SCF-CA 0.805 7.018a – –

ITSC-CA �0.107 �0.411 0.438 1.221SIC20-CA 0.052 0.670 0.108 1.102SIC25-CA �0.183 �2.218b �1.101 �0.938SIC28-CA 0.053 0.541 0.043 0.343SIC30-CA �0.026 �0.324 0.045 0.441SIC34-CA 0.040 0.498 0.055 0.539SIC35-CA �0.035 �0.318 �0.014 �0.103SIC36-CA �0.242 �1.818 �0.237 �1.414SIC37-CA �0.055 �0.581 �0.035 �0.296SIC38-CA �0.022 �0.208 �0.052 �0.398EMP_1-CA �0.041 �0.186 0.093 0.307EMP_2-CA �0.098 �0.395 0.179 0.525EMP_3-CA �0.116 �0.899 0.043 0.249

χ2¼296.991, df¼171; CFI¼0.937, NFI¼0.870; RMR¼0.044;RMSEA¼0.061, 90% CI: 0.049–0.073

χ2¼149.135, df¼73; CFI¼0.947, NFI¼0.907; RMR¼0.045;RMSEA¼0.073, 90% CI: 0.056–0.089

a po0.001.b po0.05.

Y. Jin et al. / Int. J. Production Economics 153 (2014) 24–3432

Production Flexibility (PF)PF1: Our firm's manufacturing system can operate at manyhigh and low production volumesPF2: Our firm's manufacturing system can change productionvolumes efficientlyPF3: Our firm's manufacturing system can accommodatemany different product mixesn

PF4: Our firm's manufacturing system can change productmixes efficiently

Logistics Flexibility (LF)LF1: Our firm's procurement system can fill many differentin-bound shipment requestsLF2: Our firm's procurement system can respond to changesof in-bound shipment requests efficientlyn

Suppliers' Flexibility (SF)SF1: Our suppliers can satisfy our firm's needs at many lowand high order quantitiesSF2: Our suppliers can respond efficiently to changes in ourfirm's order quantitiesSF3: Our suppliers can produce a large number of variousproducts for our firmn

SF4: Our suppliers can respond efficiently to changes in ourfirm's product variety

Supply Base Flexibility (SBF)SBF1: Our firm can quickly identify a new supplier whennecessarySBF2: Our firm can easily make adjustments in the currentrelationshipSBF3: Our firm can switch to alternative suppliers efficiently

Competitive Advantage (CA)CA1: Our firm competes with other firms by offering highquality products to our customersCA2: Our firm competes with other firms by offeringdependable delivery to our customersCA3: Our firm competes with other firms by quicklyintroducing product in the market

n Deleted item after purification in the confirmative factoranalysis.

Appendix B. Supplementary material

Supplementary material associated with this article can befound in the online version at http://dx.doi.org/10.1016/j.ijpe.2014.03.016.

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