STRENGTHENING THE INNOVATION CHAIN: THE ROLEOF INTERNAL INNOVATION CLIMATE AND STRATEGIC

RELATIONSHIPS WITH SUPPLY CHAIN PARTNERS

ADEGOKE OKEArizona State University

DANIEL I. PRAJOGOMonash University

JAYANTH JAYARAMUniversity of South Carolina

In this study, we use blended theoretical arguments from resource depen-dence theory, social capital theory, and the knowledge-based view to positthat supply chain partner innovativeness enhances a firm’s innovationstrategy which in turn positively influences innovation performance. Inaddition, we argue that the effect of supply chain partner innovativenesson product innovation strategy could be further enhanced by innovationclimate and having strategic relationships with key supply chain partners.Using data collected from 207 manufacturing firms in Australia, the find-ings show that key supply chain partner innovativeness has a positiveeffect on product innovation strategy. Further, the effect of supply chainpartner innovativeness on innovation strategy is enhanced when firmshave stronger strategic relationships with their key supply chain partners.Finally, we find that the joint influence of innovation climate and strategicrelationships with key supply chain partners enhances the effect of supplychain partner innovativeness on innovation strategy. The theoretical andpractical implications of the study are discussed.

Keywords: innovation climate; supply chain partner innovativeness; productinnovation

INTRODUCTIONInnovation is a key source of competitive advantage

(Bowonder, Dambal, Kumar, & Shirodkar, 2010;Duane Ireland & Webb, 2007; Lengnick-Hall, 1992;Tidd, Bessant, & Pavitt, 2005). Despite the manyproblems of managing it, innovation has becomeimperative for many companies. Research evidencehas identified a range of benefits for those companiesthat have been able to successfully exploit innovationstrategies to realize higher profits and market share(Cho & Pucik, 2005; Damanpour, Walker, & Avellane-da, 2009). The question is no longer one of whetheror not to innovate but rather how to strategize forinnovation in order to achieve competitive advantagefor organizations. In particular, due to the complex

nature of innovation strategies, the roles of externalconstituents such as suppliers and customers haveemerged to be vital to the success of the focal firm’sinnovation strategy (von Hippel, 1986; Vega-Jurado,Guti�errez-Gracia, Fern�andez-de-Lucio, & Manjarr�es-Henr�ıquez, 2008).The attention of previous studies has been focused

on identifying internal antecedents of innovationcapability and performance. For example, the influ-ence of leadership styles (Oke, Munshi, & Walumbwa,2009), organizational processes (Jespersen, 2012;Tyagi & Sawhney, 2010), and human capital(Beugelsdijk, 2008; Chong, Eerde, Rutte, & Chai,2012) on innovation performance has beenrecognized. However, organizations are becoming

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increasingly networked with an increase in the num-ber and intensity of collaborations for innovationsand new product development (NPD). Accordingly,there is an emerging body of literature focusing onantecedents of innovation in organizational networks,most particularly supply chain networks (Pittaway,Robertson, Munir, Denyer, & Neely, 2004). As suchthere is a need to investigate the influence of supplychain factors on a firm’s innovation performance(Craighead, Hult, & Ketchen, 2009).Previous studies have investigated the effects of inte-

grating suppliers into a firm’s NPD process (Jayaram,2008; Petersen, Ragatz, & Monczka, 2005; Wagner,2012). However, beyond full integration of suppliersinto the NPD process through their engagement withkey suppliers, firms may actually tap or learn from theinnovativeness of their suppliers. Similarly, focal firmsrely on the expertise of suppliers and customers toweed out failing products. For example, Wal-Martshares key worldwide sales information with its strate-gic suppliers such as Procter and Gamble. This helpsProcter and Gamble to decide on their own innova-tion strategies as far as what is likely to sell and whatis not likely to sell (Hougland, 2007). Drawing fromresource dependency theory (Paulraj & Chen, 2007a;Pfeffer & Salancik, 2003) and the knowledge-basedview (KBV) (Grant, 1996b), we argue that firms maydepend on and tap from the innovativeness of theirsupply chain partners to strategize for innovation andenhance their innovation performance (Azadegan &Dooley, 2010). Limited capacity for innovation,shorter time to market, and the need to share risksassociated with innovation development are drivingfirms to seek innovations from their supply chainpartners (Koufteros, Rawski, & Rupak, 2010; Koufter-os, Vonderembse, & Jayaram, 2005; Wagner, 2010,2012).In this study, our focus is on supply chain partners

that may include suppliers and customers in a firm’ssupply chain. We define a supply chain partner’sinnovativeness in terms of the extent to which thesupply chain partner possesses the ability to producenew ideas and innovations. This ability has the poten-tial to channel innovation pathways for focal firms aswell. This is so because increasingly the locus of fun-damentally innovative ideas stem from the supplychain. For example, the innovations part of the “Intelinside” program benefitted many PC manufacturers.The innovation in the business model of CHEP whichrevolutionized global pallet management with the“lease anywhere and return anywhere” concept hadimportant implications on supply chain design for itscustomers. Thus, we argue that tapping innovativeknowledge from supply chain partners to strategizefor innovation will have an effect on a firm’s innova-tion performance. More importantly, building on the

works of Azadegan, Dooley, Carter and Carter (2008),Wagner (2012) and Azadegan (2011), we posit thatexploiting supply chain partner innovativeness tostrategize for innovation is contingent upon two keyfactors. First, drawing from social capital theory (Law-son, Tyler, & Cousins, 2008), we posit that buildingstrategic relationships and trust with key supply chainpartners will enhance the effective tapping andexchange of knowledge with such firms (Bensaou,1999). We define “strategic relationship with supplychain partners” in terms of the extent to which therelationship is enduring and on a long-term basis(Choi & Hartley, 1996; Paulraj & Chen, 2007b). Dueto the risky nature of innovation efforts and the needto protect intellectual properties in the innovationprocess, suppliers are more likely to align with cus-tomers for innovation if there is a long-term relation-ship effort in place.Second, we argue that a culture of innovation pro-

vides an environment where supply chain partnerinnovativeness can be effectively tapped to implementproduct innovation strategies (Azadegan, 2011). Wedefine innovation climate in terms of the extent towhich the firm encourages and builds a climate thatsupports innovation (Cho & Pucik, 2005; Riordan,Vandenberg, & Richardson, 2005). Finally, productinnovation strategy is defined in terms of the extent towhich the firm uses new components, new materials,new technologies, and new product features in thedevelopment of a product (OECD, 2005), while prod-uct innovation performance is defined in terms of thenovel products and the number of new products actu-ally produced or developed by a firm.It is pertinent to note that in our study, product

innovation strategy and product innovation perfor-mance are distinctly separate constructs. Product inno-vation strategy relates to what a firm does in terms ofobtaining novel products (product innovation perfor-mance) including the specific actions and activitiesthat are implemented in order to obtain improvedinnovation performance. Thus, in our study, wehypothesize product innovation strategy as an ante-cedent of innovation performance. Taken together,this study aims to investigate (a) the effect of supplychain partner innovativeness on a firm’s innovationstrategy; (b) the separate and combined moderatingroles of the strategic relationship with a supplier andinnovation climate in enhancing the effect of supplychain partner innovativeness on innovation strategy;and (c) the effects of implementing a product innova-tion strategy on a firm’s innovation performance. Ourstudy seeks to contribute to the extant literature ondeveloping and building firms’ innovation perfor-mance through engaging with supply chain partners.Specifically, while much is known about the linkbetween suppliers’ innovativeness and performance

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(e.g., Azadegan & Dooley, 2010; Lau, Tang, & Yam,2010), little is known about the processes (e.g., prod-uct innovation strategy in our study) through whichsupply chain partners’ innovativeness relate to perfor-mance. Our study fills this gap in the literature.Further, the investigation of the influence of thecombined effects of internal innovation climate andstrategic relationships as moderators of the linkbetween supplier chain partners’ innovativeness andproduct innovation strategy represents contributionsto and extends the body of work that focuses ontapping innovation and knowledge from external part-ners such as suppliers (Brown & Eisenhardt, 1995).In the next section, we discuss the theoretical frame-

work and develop our hypotheses. Next, we presentthe methodology. Following that we present anddiscuss the results of the study and conclude bydiscussing the theoretical and practical implications ofthe study.

THEORY AND HYPOTHESES

Supply Chain Partner Innovativeness andProduct Innovation StrategyIn explicating the relationship between supply chain

partner innovativeness and product innovation strat-egy, we first draw from resource dependency theory(RDT) (Pfeffer & Salancik, 2003). According toresource dependency theory, interorganizational linkscan be described as a set of power relations based onthe exchange of resources (Pfeffer & Salancik, 2003).As firms may not have all the resources needed forcompetitiveness at their disposal, they will seek tobuild relationships with others such as firms withinthe supply chain that possess key needed resources(Azadegan, Napshin, & Oke, 2013).Innovativeness or the ability to develop new prod-

ucts and innovations is a vital resource that firms seekto gain competitiveness (Avlonitis, Papastathopoulou,& Gounaris, 2001; Cho & Pucik, 2005; Santos-Vijande& Alvarez-Gonzalez, 2007). Firms lacking this vitalinnovative capability will seek to tap innovative part-ners. The examples of Intel and CHEP that were high-lighted in an earlier section illustrate the connectionbetween supply chain partner innovativeness and afocal firm’s innovation strategy. For example, supplierinnovativeness has become a key factor in supplierevaluation and the prequalification process (Azadegan,2011). Indeed, the process of aligning with the inno-vative capabilities of suppliers is not only an initialprocess (at the time of screening) but also an ongoingprocess.Engaging with innovative suppliers can expose buy-

ers to suppliers’ innovations that can increase thebuyer’s innovative capability (Azadegan, 2011). Inno-vative suppliers are able to supply buying firms with

components at the leading edge of technology whichthe firms can integrate into their production process(Hoetker, 2005). Similarly, a focal firm’s innovativecustomers can be important resources for innovations(von Hippel, 1986; Napolitano, 1991). The case stud-ies of innovations in the fields of education, medi-cine, and welfare using IT and multimedia technologyin Japan (Kodama, 2002) demonstrate the importanceof building strategic partnerships with customers whoare highly knowledgeable about the products andservices to create new business models as well asreaching out to many other associated customers.Customers are closer to the market and understandthe market well; thus, they are able to offer valuableinput into a firm’s innovative processes. Collectively,this suggests the potential for an orchestration of aknowledge network with each part fulfilling the roleassigned to them.Resource dependency theory (RDT) views organiza-

tions as coalitions in which structures and patterns ofbehavior are molded to acquire needed externalresources (Pfeffer & Salancik, 2003). RDT is an appro-priate theoretical lens to employ to investigate the tap-ping of partners’ innovativeness because according toRDT, suppliers will try to increase the buyer’s depen-dency on their operations by continuously offeringvalue in the form of innovations. On the other hand,the buyer will attempt to decrease its dependence onthe supplier or customers by seeking to develop andincrease the vital resource—innovative capability—which these supply chain partners offer. In otherwords, organizations will alter their patterns of behav-ior to reduce their dependence on others for vitalresources by implementing innovation strategies toenhance their performance. This suggests that focalfirms that have neither the technical know-how northe intention to pursue innovations that are betterhandled via outsourcing will likely increase theirdependence on their supply chain partners. Exposureto supply chain partners that have innovative ideasand offer new technologies and components will notonly drive firms to implement and utilize these newtechnologies in product development (Lau et al.,2010; Tan & Tracey, 2007) but also trigger them tofind ways of developing capabilities in innovation.Second, we draw from the KBV (Grant, 1996b;

Nonaka, 1994) to further examine how supply chainpartners’ innovativeness links with a firm’s productinnovation strategy. The KBV is an appropriate theo-retical lens to use because the transfer and flow ofknowledge is at the core of innovative activities andthe KBV considers the creation, integration, and appli-cation of knowledge as the principal function of thefirm (Grant, 1996a; Nonaka, 1994). A key tenet ofthe KBV is that organizations engage in routineswhich help to enhance learning through repeated

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performance (Oke & Kach, 2012). Collaborations withinnovative supply chain partners enable a firm to beconsistently exposed to innovative behaviors of thepartners which the firm can acquire, learn, and inter-nalize to strategize for innovation. In other words, afirm can exploit and reconfigure external knowledgeto enhance its own internal capabilities for developingproduct innovations.Taken together, the theoretical arguments support

the notion that supplier chain partner innovativenesscan trigger firms to have innovation strategies, leadingto the following hypothesis:

H1: Supply chain partner innovativeness has apositive relationship with the focal firm’s productinnovation strategy.

The Influence of Innovation Climate andStrategic Relationship with Supply ChainPartners on the Supply Chain PartnerInnovativeness–Innovation Strategy LinkThe relationship between supplier innovativeness

and a buyer’s manufacturing performance and themoderating roles of interorganizational learning,supplier evaluation, supplier integration, and absorp-tive capacity have been the focus of recent studies(Azadegan, 2011; Azadegan & Dooley, 2010; Koufteroset al., 2010; Wagner, 2012). Yet, the role of contin-gency factors such as innovation climate (Bain, Mann,& Pirola-Merlo, 2001) and strategic relationship withsupply chain partners as moderators of the relation-ship has not been studied. To better utilize and tapsupply chain partner innovativeness, firms mustdevelop complementary skills and have an orientationtoward innovation by providing support for innova-tion and fostering an environment where innovationthrives (Amabile, 1998). Such an orientation towardinnovation increases the learning capability within

firms and enables firms to better understand and ger-minate partners’ innovative ideas that translate intomore efficient production processes. Indeed, suppliersare more likely to offer innovative ideas to buyer firmsthat have a culture of innovation and recognize thevalue of such ideas and new technologies (Kodama,2002; Lindgreen, Antioco, Palmer, & Heesch, 2009).A similar argument can be made with respect to the

downstream part of the innovation network byinvolving customers in the product innovation effortsof focal firms (Koufteros et al., 2005). Such aninvolvement is more likely to take place in focal firmsthat have a strong internal climate for innovation.Thus, an organizational environment that supportscross-fertilization of ideas and stimulates creativity islikely to provide a good fertile ground for supplychain partners’ innovative offerings to firms (Su,Tsang, & Peng, 2009). Indeed, according to the KBV,when outside knowledge is “intertwined” with thatresiding inside the organization and fostered by aninternal innovation climate, it can lead to learningthat can enhance innovation performance (Jones &Macpherson, 2006; Morgan, Zou, Vorhies, & Katsik-eas, 2003). In sum, the positive effect of supply chainpartner innovativeness on a firm’s use of innovativeofferings to develop new products (product inno-vation strategy) is likely to be enhanced in an organi-zational environment where innovation thrives,which leads us to the next hypothesis which is statedbelow. This posited interaction effect is also shown inFigure 1:

H2: An innovation climate will positively moderatethe relationship between supply chain partnerinnovativeness and product innovation strategy.

Social capital theory suggests that firms can moreeffectively tap knowledge or capabilities from otherfirms if they can successfully build social capital (in

FIGURE 1Research Framework

SC partner innovativeness

Product Innovation

Performance

Product Innovation Strategy

Innovative climate

Strategic relationship

Innovative climate × Strategic

relationship

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terms of relationship and trust) with those firms (Kra-use, Handfield, & Tyler, 2007). Under social capitaltheory, strategic relationships need to be built as a cat-alyst for tapping the innovative potential of supplychain partners. As relationships with supply chainpartners become more enduring and long term,mutual trust is developed and the partners becomemore conversant with the focal firms’ patterns ofbehavior and product offerings.According to the KBV, such relationships enable end

customers and suppliers to be able to share and offerthe required expertise to a firm which the firm caninternalize and utilize in its product development.Similarly, the focal firm gains more insight intosuppliers’ innovative processes and is able to tap fromsuppliers’ knowledge, exploit, and reconfigure it inorder to increase its own innovative capability(Knudsen, 2007). Within this relationship model,joint projects may be undertaken that will inevitablylead to the use of innovative offerings to develop newproducts (product innovation strategy) (Lau et al.,2010). Indeed, Azadegan (2011) argues that estab-lished relationships with suppliers enable suppliers’innovativeness to become a relational asset which canbe complementary and increase a firm’s performance.Similarly, the works of Wagner and Buk�o (2005) andTan and Tracey (2007) have argued for collaborativenetworks of NPD that involve customers as well.Therefore, we posit here that strategic relationshipswith key innovative supply chain partners will enablefirms to more effectively gain or tap innovative ideasfrom these partners, thus enhancing the propensity ofa firm to implement innovation strategies (Van deVen, 1986). Thus, we offer the following hypothesisand show this interaction effect in Figure 1:

H3: Strategic relationships with supply chain part-ners will positively moderate the relationshipbetween supply chain partner innovativeness and afirm’s product innovation strategy.

Synergistic Effects of Innovation Climate andStrategic RelationshipsIn the following hypothesis, we argue for a joint

moderating influence of the interaction between orga-nizational innovation climate and relationship withsupply chain partners on the link between supplychain partner innovativeness and product innovationstrategy. The premise for this argument is that forfirms that have joint investments in both internalorganizational innovation climate and external strate-gic relationships with suppliers, the effect of supplychain partner innovativeness on product innovationstrategy is stronger than for firms without these invest-ments. The study by Wagner and Buk�o (2005) shows

that strategic relationships with supply chain partners(customers and suppliers) in the form of knowledgesharing is influenced (moderated) by organizationalresource commitment. Implicit in this notion is theinteraction between organizational innovative climateand the innovativeness of supply chain partner ininfluencing innovation strategy of the firm. This argu-ment also stems from the matched domains argument(Koufteros, Vickery, & Droge, 2012) and the innova-tion chain precepts (Azadegan & Dooley, 2010; Wyn-stra, von Corswant, & Wetzels, 2010). Both of theseprecepts argue for an alignment in structures inter-nally and externally to enhance joint innovationprogress.Further, according to the KBV, firms are able to tap

from a supply chain partner’s innovativeness if theyare repeatedly exposed to the partner’s knowledgebase. Such exposure is possible only through enduringor strategic relationships between the two entities.Internal innovation climate enables a firm to effec-tively tap, internalize, and exploit such externalknowledge to develop and improve innovation inter-nally. Thus, strategic relationships with key supplychain partners will combine with internal innovationclimate to enhance the exploitation of the supplychain partner innovativeness to improve a firm’sinnovation capabilities. Accordingly, we present thefollowing hypothesis and show this interaction effectin Figure 1:

H4: The joint interaction of innovation climateand strategic relationships with supply chain part-ners will positively moderate the relationshipbetween supply chain partner innovativeness andproduct innovation strategy.

Linking Product Innovation Strategy to ProductInnovation PerformanceImplementing product innovation strategies through

the use of new components and new materials inproduct development enables the reconfiguration ofproduct architecture and composition of the finalproduct which could result in highly innovative andnovel products (Chen, Chen, & Vanhaverbeke, 2011;Oke, Walumbwa, & Myers, 2012; Tsai, Hsieh, & Hult-ink, 2011). Using new materials and components thathave a wide range of applications in product develop-ment can also enhance the number of new productsproduced as well as the overall performance of thefinal products (Millson & Wilemon, 2008; Song, Song& Benedetto, 2011). Newspaper wood is a set of novelwood products that have resulted in novel furnitureand home products. These products that includelamps, chairs, and other home products are developedfrom new materials—in this case, recycled newspapers

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(not cut and dried wood) that have been meticulouslyand individually glued together, rolled into a tight“log” and left to dry, deform and harden just like liv-ing trees would do. Thus, a strategy of using newmaterials in product development can result in novelproducts.Similarly, firms can strategize for innovation using

new technologies that have a wide range of applica-tions leading to novel products and an increase in thenumber of new products derivable from those tech-nologies (Judi & Beach, 2010). The introduction oftouchscreen technology has revolutionized manyproducts and changed many industries. Through theuse of touchscreen technology, novel products such aspersonal computer tablets and smart phones, includ-ing Apple’s I-Pad and I-Phone, have been developed.Similarly, the use of gesture-based computer controltechnology that allows active interaction with a com-puter through natural human gestures has revolution-ized the gaming industry leading to novel productslike Microsoft’s Xbox Kinect body sensor and Ninten-do’s Wii handheld control sensor (Mitra & Acharya,2007). In other words, implementing innovation strat-egy through the use of technology in product develop-ment offers opportunities for novel products andimproved innovation performance.Taken together, we offer the following hypothesis:

H5: Product innovation strategy has a positive rela-tionship with product innovation performance.

The Mediating Role of Product InnovationStrategyAs we have previously noted, prior studies on tap-

ping supplier innovativeness or integration of suppli-ers into the NPD process have considered the directinfluence of these factors on a focal firm’s manufactur-ing performance (Parker, Zsidisin, & Ragatz, 2008;Petersen, Handfield, & Ragatz, 2003). Similarly, theeffect of tapping customer innovativeness on innova-tion performance has been examined in several stud-ies (Blazevic & Lievens, 2008; Elofson & Robinson,2007). Largely missing in these studies are the pro-cesses by which the innovativeness of these supplychain partners influence other performance outcomes.Our first hypothesis in this study identifies the

implementation of product innovation strategy, com-prising the use of new technologies, new product fea-tures, and components in product development, as adirect consequence of tapping supply chain partnerinnovativeness. To develop this hypothesis, we drawfrom resource dependence theory (Pfeffer & Salancik,2003) and argue that firms strive to reduce theirdependencies on supply chain partners’ innovative-ness by developing their own product innovation

strategies to attain an improved innovation perfor-mance. In addition, we argue that when firms imple-ment specific innovation initiatives in productdevelopment (product innovation strategy), animprovement in product innovation performance canbe attained. Taken together, these arguments suggestthat a firm’s product innovation strategy is both aconsequence of supply chain partners’ innovativenessand an antecedent of product innovation perfor-mance. The implication of this is that product innova-tion strategy is a process or a mechanism throughwhich supply chain partners’ innovativeness affects afirm’s innovation performance. As we noted above,prior research has mainly focused on the direct linkbetween external sources of innovation and a firm’sinnovation performance (Kodama, 2002; Lau et al.,2010; Oke & Kach, 2012).The direct link between external sources of innova-

tion and performance may be due to several factorsother than product innovation strategy. For example,collaborating with an innovative supply chain partnercould enhance a firm’s learning and absorptive capac-ity which may enhance the firm’s capability toimprove its innovation performance. In other words,apart from product innovation strategy, other mecha-nisms exist through which supply chain partners’innovativeness relates to a firm’s innovation perfor-mance. This suggests that product innovation strategyis a partial mediator of the link between a supplychain partner’s innovativeness and innovationperformance. Accordingly, we offer the followinghypothesis:

H6: Product innovation strategy partially mediatesthe link between supply chain partner innovative-ness and product innovation performance.

The research model tested in this study is presentedin Figure 1.

METHODS

Sample and ProceduresThis study utilized a cross-sectional mail survey of a

sample of Australian manufacturing firms, encompass-ing various sectors, including food, electronics, wood,textiles, plastics, metal, and pharmaceuticals withinthe scope of the Australia and New Zealand StandardIndustrial Classification (ANZSIC) codes under Divi-sion C (Manufacturing). Table 1 shows the sampledistribution of the manufacturing sectors captured inthis study. In administering our survey, we specificallyrequested in the cover letter of the survey that thequestionnaire be assigned to middle and seniormanagers whose primary responsibilities are related tostrategic innovation activities of the firms. In total,

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1,000 surveys were mailed out, and 207 usableresponses were received representing an effectiveresponse rate of 20.7%.

Nonresponse BiasTo test for nonresponse bias, we compared the

responses of early and late waves of returned surveysbased on the assumption that the opinions of laterespondents are representative of the opinions of non-respondents (Armstrong & Overton, 1977). Student’st-tests yielded no statistically significant differencesbetween early-wave and late-wave groups with respectto firm’s size and several key variables, including busi-ness performance. The results of the t-tests suggest thatnonresponse bias was not a problem in this dataset.

MeasuresAll measures used in this study were derived from

previous studies to secure their content validity. Themeasure for supply chain partner innovativeness wasderived from the studies by Azadegan and Dooley(2010) and Wang and Ahmed (2004). In addressingthis scale, we specifically asked respondents to focuson the firm’s most valuable supply chain partner (i.e.,the buyer or supplier with whom their firm conductsmaximum business in dollar terms). The measure forstrategic relationship was derived from the supply

chain management literature (Chen & Paulraj, 2004;Fynes, Voss, & de B�urca, 2005; Li, Rao, Ragu-Nathan,& Ragu-Nathan, 2005) which emphasized the impor-tance of building long-term relationships and strategiccollaborations with the firm’s most valuable supplychain partners for mutual benefits. In measuring inno-vative climate, we adopted the scale by Prajogo andAhmed (2006) which includes several key practicessuch as providing resources for employees to generateinnovative ideas and to facilitate knowledge and ideasharing through open communications. The scale forproduct innovation strategy was derived from Akg€un,Keskin and Byrne (2009), Gunday, Ulusoy, Kilic andAlpkan (2011), and Yamin, Mavondo, Gunasekaranand Sarros (1997), and it reflects several key practicesthat firms employ to develop new and innovativeproducts, including the use of new components, newmaterials, and new technologies.Product innovation performance is measured in

terms of the quantity and innovativeness of new prod-ucts developed and introduced to the market (Gopala-krishnan, 2000; Prajogo & Sohal, 2006; Spanjol,Qualls, & Rosa, 2011), for which we asked respon-dents to assess their performance relative to the indus-try average using 7-point Likert-type scale from 1(well below) to 7 (well above). The items used to cap-ture each scale are presented in Table 2.

RESULTS

Scale Validity and ReliabilityAs a first step, we performed validity and reliability

tests on the five measures used in this study usingconfirmatory factor analysis (CFA). The results of theCFA and measures of Cronbach’s alpha are presentedin Table 2. The normed chi-square value(v2 = 201.01; df = 142) is <3. The fit indices(NFI = .937, NNFI = .974, CFI = .978, GFI = .907)are also above the cutoff score for an acceptablemodel (.90) with most of the indices even exceedingthe cutoff score for a good model (.95). The RMSEAvalue is .045, well below the recommended cutoffpoint of .08. The overall model fit results suggestacceptable unidimensionality and convergent validityfor the measures (Bagozzi, Yi, & Philips, 1991; Bollen,1989; Carmines & McIver, 1981; Hoskisson, Hitt,Johnson, & Moesel, 1993). The results also show thatall items loaded significantly on their respective con-structs with standardized path loadings above .5. Thefive scales also showed a strong reliability as indicatedby Cronbach’s alpha values which surpassed thethreshold point of .70 (Nunnally, 1978). We alsocomputed composite reliability using the standardizedloadings and the measurement error of each indicator,and the results show that the five constructs havecomposite reliabilities above .7 (Hair, Black, Babin,

TABLE 1

Sample Distribution of the Manufacturing Sec-tors Based on Australia and New Zealand Stan-dard Industrial Classification (ANZSIC) Codes

Manufacturing SectorsBased on ANZSICCodes

Numberof Firms

Valid % ofthe Sample

Food, beverage, andtobacco

49 23.7

Textile, clothing,footwear, and leather

7 3.4

Wood and paper 9 4.3Printing, publishing,and media

11 5.3

Petroleum, coal, andchemical

20 9.7

Nonmetallic mineral 5 2.4Metal 12 5.8Machinery andequipment

42 20.3

Prefabricated building,furniture, and others

48 23.2

Construction 4 1.9Total 207 100

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Anderson, & Tatham, 2006). Next, we computed theaverage variance extracted (AVE) for each constructusing the squared standardized loadings and the mea-surement error of each indicator to further confirmthe scale validity; these results show that the AVEs forthe five scales are greater than the recommended valueof .50 (Fornell & Larker, 1981).As the data were provided by a single respondent in

each responding firm, we needed to check whetherthe responses would be affected by common method

bias using the Harmann’s single-factor test (Paulraj,2011; Podsakoff, MacKenzie, Jeong-Yeon, & Podsak-off, 2003). This test was run by loading all 19 itemsinto one factor as a competing model for the CFAmodel. The common model produced a poor fit tothe data (chi-square (v2) = 1,828.88, df = 152,RMSEA = .231). In addition, a large portion of theindicators has poor factor loadings (.3 or below).These results suggest that common method variancewas not a significant problem in the dataset.

TABLE 2

Scale Validity and Reliability

Scales Items

StandardFactorLoading

Cronbach’sAlpha

Supply chainpartner’sinnovativeness

Our supply chain partner adopts innovation as their primarystrategy.

.81 .90

Our supply chain partner uses cutting edge technologies inthe industry.

.77 (.91)a

Our supply chain partner continuously produces new ideas. .86 (.66)b

Our supply chain partner gains a large portion of revenuefrom new products.

.74

Our supply chain partner is recognized as being innovative. .88Organizationalinnovativeclimate

Our company provides time and resources for employees togenerate, share/exchange, and experiment with innovativeideas/solutions.

.75 .78

Our employees are working in diversely skilled work groupswhere there is free and open communication among thegroup members.

.83 (.84)a

(.57)b

Our employees frequently encounter nonroutine andchallenging work that stimulates creativity.

.75

Our employees are recognized and rewarded for theircreativity and innovative ideas.

.69

Strategicrelationshipswith supplychain partners

We expect our relationship with the key supply chainpartners to last a long time.

.76 .78

We collaborate with the key supply chain partner toimprove performance in the long run.

.70 (.81)a

(.51)b

The supply chain partner sees our relationship as a long-term alliance.

.81

We view our supply chain partner as an extension of ourcompany.

.57

Productinnovationstrategy

We develop or use new components. .78 .85We develop or use new materials (including green/recycledmaterials).

.68 (.85)a

We develop or use new technologies in our products. .79 (.59)b

We develop or use new product features. .81Innovationperformance

Novelty of new products .78 .78Number of new products introduced .82 (.78)a

(.64)b

aCR, composite reliability.bAVE, average variance extracted.v2 = 201.01, df = 142, RMSEA = .045, NFI = .937, NNFI = .974, CFI = .978, GFI = .907.

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A discriminant validity test was performed to exam-ine whether constructs were distinct from each other.We followed the method used by Ahire, Golhar andWaller (1996) by pairing each of the constructs andsubjecting them to two (CFA) measurement models.All of the tests results passed the criterion for discrimi-nant validity (p < .01).The second step was to generate the composite

scores for the five scales which were used in theregression analysis, using the mean score (Hair et al.,2006). The normality of the five composite scores wastested, and we found no violation of normality asindicated by skewness and kurtosis values which arewithin the accepted range (�1 and <7, respectively).As the data were obtained from different manufac-

turing sectors, we conducted a preliminary test usingMANOVA to check whether there was any differenceacross the above five composite variables betweendifferent manufacturing sectors. The MANOVA wasstatistically significant (Pillai’s Trace F = 1.01, p < .05,Wilks’ Lambda F = 1.01; p < .05, and Hotelling’sTrace F = 1.01, p < .01). Following Tabachnick andFidell (2007), follow-up MANOVAs were conductedusing the Bonferroni test, and the results showed thatnone of the five variables was significantly different(at p < .05) between manufacturing sectors. Overall,the results of MANOVA test suggest that it is appropri-ate to pool the data in the analysis.Prior to conducting the regression analysis, we per-

formed Pearson bivariate correlations between all vari-ables included in this study (including organizationalsize as a control variable). These correlations are pre-sented in Table 3. Overall, the correlation coefficientssuggest there is no multicollinearity among thesevariables which could affect the regression.

ANALYSISStructural equation modeling (SEM) was used to test

the hypotheses relating to direct and indirect effects.We employed SEM because this approach allows esti-

mation of all the relationships simultaneously toaccount for any potential measurement error asopposed to testing the model in a piecemeal fashion.It is also pertinent to note that SEM approach pro-vides the best balance of type I error rates and statisti-cal power when testing direct and indirect effects(James, Mulaik, & Brett, 2006; MacKinnon, Lock-wood, Hoffman, West, & Sheets, 2002). We used hier-archical moderated regression to test for interactioneffects. This approach helps to provide effect sizeassessment and has been used in a similar way inother research studies that include investigation ofmoderator variables.

Structural Equation Modeling (Tests for H1, H5,and H6)We used SEM to test the relationships among the

supply chain partner’s innovativeness, strategic rela-tionship, innovative climate, product innovation strat-egy, and product innovation performance. The focalfirm’s size was used as a control variable for bothproduct innovation strategy and product innovationperformance. The results displayed in Figure 2 show agood fit (v2 = 73.40, df = 49, RMSEA = .049, NFI =.959, NNFI = .979, CFI = .985, and GFI = .944). Sup-ply chain partner’s innovativeness has a positive effecton product innovation strategy (b = .34 at p < .01).Thus, H1 is supported. Furthermore, product innova-tion strategy shows a positive relationship with prod-uct innovation performance (b = .44 at p < .01),supporting H5. The results also show that a supplychain partner’s innovativeness has a direct, positiveeffect on product innovation performance albeit rela-tively weaker than the effect of product innovationstrategy (b = .18 at p < .05). This direct effect suggeststhat product innovation strategy partially mediates theinfluence of supply chain partner innovativenesson innovation performance, which indicates supportfor H6.A further test was conducted by comparing this par-

tially mediating model with another model where the

TABLE 3

Correlation Matrix

Mean SD 1 2 3 4 5

Firm size 1 3.76 1.77 –Organizational innovative climate 2 4.57 1.09 �.04 –Supply chain partners innovativeness 3 3.96 1.14 �.15* .15* –Strategic relationship 4 5.61 .81 �.17* .12 .27** –Product innovation strategy 5 4.79 1.15 �.01 .47** .30** .20** –Product innovation performance 6 4.08 1.23 .06 .33** .27** .10 .40**

*p < .05, **p < .01.

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direct paths between the three independent variables(supply chain partner’s innovativeness, innovative cli-mate, and strategic relationship) and the dependentvariable (product innovation performance) wereremoved (i.e., a fully mediating model). This modelproduced a slightly higher chi-square value (78.18with df = 50). The chi-square difference between thepartial and the fully mediating models is 4.68 (df = 1,p < .05). Thus, H6, which posits that product innova-tion strategy partially mediates the associationbetween supply chain partners’ innovativeness andinnovation performance, is supported.

Hierarchical Moderated Regression Analysis(tests for H2, H3 & H4)In testing the hypotheses, we ran three different sets

of multiple regression models. We consider organiza-tional size as a control variable for all regression mod-els tested in this study. The first regression modelaims to confirm the results of the SEM analysis pre-sented previously. These results are presented inTable 4. Supply chain partner innovativeness shows apositive effect on product innovation strategy (b = .23at p < .01).The second regression model tests the moderation

hypotheses included in this study (H2, H3, and H4).In this regard, we calculated three interaction variablesthat comprise two two-way interactions (i.e., betweeninnovative climate and supply chain partner innova-tiveness and between supply chain partner innovative-ness and strategic relationship) and one three-wayinteraction (i.e., between innovation climate, strategicrelationship, and supply chain partner innovative-ness). Prior to this process, all variables involved werestandardized to minimize potential multicollinearitybetween the independent variables and their productterms (Tabachnick & Fidell, 2007). We also checkedfor multicollinearity by examining variance inflationfactors (VIFs) for all the variables. All VIF values werelower than 2, thus well below the recommended

cutoff of 10, confirming that multicollinearity is not aproblem in our results.The results of the moderated regression analysis are

presented in Table 4. The interaction between supplychain partner innovativeness and innovative climatehas no effect on product innovation strategy(b = �.04 at p > .05); thus, H2 is not supported. Onthe other hand, the interaction between supply chainpartner innovativeness and strategic relationship has apositive effect on product innovation strategy (b = .21at p < .01); thus, H3 is supported. Finally, the three-way interaction between supply chain partner innova-tiveness, innovative climate, and strategic relationshiphas a positive effect on product innovation strategy(b = .14 at p < .05); therefore, H4 is supported.

FIGURE 2Structural Equation Modeling Results

SC partner innovativeness

Product Innovation Performance

Product Innovation Strategy

0.18*

0.34** 0.44**

Organizational size

0.10 0.03

χ2 = 73.50, df = 49, RMSEA = 0.049, NFI = 0.959, NNFI = 0.979, CFI = 0.985, GFI = 0.944

TABLE 4

Hierarchical Moderated Regression Analysis

ProductInnovationStrategy

Organizational size .04 .01Supply chain partnerinnovativeness

.30** .23**

Organizational innovative climate .45**

Strategic relationships withsupply chain partners

.09

SC partner innovativeness 9

innovative climate�.04

SC partner innovativeness 9

strategic relationships.21**

SC partner innovativeness 9

innovative climate 9 strategicrelationships

.14*

R2 .10 .34

*p < .05, **p < .01.

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DISCUSSION AND CONCLUSIONThe precepts of resource dependence theory, the

KBV, and social capital theory were used to argue forthe links between supply chain partner innovative-ness, the implementation of product innovation strat-egy, and product innovation performance of a firm.This is consistent with the work of Tan and Tracey(2007) who found that involving customers andsuppliers in collaborative NPD projects had a positiveinfluence on performance. We find support for thenotion in this study that supply chain partner inno-vativeness positively relates to product innovationperformance through product innovation strategy.Firms depend on their supply chain partners forinnovative input. The dependency on supply chainpartners’ innovativeness triggers firms to implementproduct innovation strategies of their own in orderto reduce the dependency. Further, a firm’s exposureto and dependency on innovative partners enable thefirm to develop routines and garner relevant knowl-edge that can be exploited and intertwined withinternal knowledge to implement its own productinnovation strategies including using new compo-nents, materials, and new technologies in productdevelopment.While the theoretical arguments justify the key rela-

tionship that ties supply chain partner innovativenessto the focal firm’s innovation strategy, we extend thisidea by addressing the “how” of this phenomenon.For example, we argue that an appropriately designedinternal climate for innovation will further strengthenthe innovation chain that links supply chain partnerinnovativeness to the innovation strategy of the focalfirm. Next, building strategic relationships with supplychain partners to tap into the innovative base of thesesupply chain partners sets the right external climate.This is so because the foundation of knowledge shar-ing across network partners cannot take place withouta climate of cooperation and trust across the entireinnovation chain (Wagner & Buk�o, 2005).Taken together, our study is perhaps the first to

complement the innovation chain with the notion ofa climate chain. In other words, the internal climatefor innovation should align and blend well withefforts made externally with key suppliers for tappinginto ideas for new innovations. However, these claimswere modified when our results found no support forthe moderating influence of internal innovation cli-mate but found full support for the moderating influ-ence of building strategic relationships with supplychain partners. An explanation for the insignificantfinding is that at the margin, an appropriatelydesigned internal innovation climate is a “given” andtherefore does not further explain the positive influ-ence of supply chain partner innovativeness on focal

firm’s innovation strategy. In contrast, building trustand relationships with external constituents serves asa catalyst for tapping the innovative potential of sup-ply chain partners. Strategic relationships enable focalfirms and their partners to become more conversantwith each other’s organizational processes and pat-terns of behaviors, and more willing to share ideasand innovative practices. This enhances the positiveinfluence of supply chain partners’ innovativeness ona focal firm’s innovation strategy.It is interesting to note that the joint investment in

internal innovation climate and building relationshipswith supply chain partners moderates the relationshipbetween supply chain partner innovativeness andproduct innovation strategy. In other words, the influ-ence of innovative climate on supply chain partnerinnovativeness will be more effective when there is astrategic relationship between the focal firm and itsinnovative supply chain partner. As we have notedabove, building strategic relationships appears to be akey ingredient in enhancing a firm’s innovative capa-bility from supply chain partner innovativeness. It isconceivable that for many product and process tech-nologies, the locus of innovation, at the margin, lieswith the external supply chain partners, which meansthat building strategic relationships with partners ismore important than having an internal innovativeclimate. Although an investment in internal innova-tive climate by itself does not strengthen the innova-tion chain, we find that such an investment is equallynot detrimental. In other words, both investments ininternal innovation climate and strategic relationshipswith partners (external climate) are needed tostrengthen the innovation chain.This study contributes to knowledge by extending

the notion of supply chains and value chains tospecifically understand what happens in innovationchains. In particular, what mechanisms substantiallyenhance supply chain partners’ efforts on the focalfirm’s efforts to innovate? Our results point to thepowerful combinatorial influence of two factors—oneinternal and another external—that further strengthenthe innovation chain. Internal innovative climate fac-tors specifically motivate firms to encourage “out ofthe box” and lateral thinking, and promote employeesto engage in high-risk innovative ideas. For example,firms such as Google, 3M, and AT&T have a long-standing tradition of creating workplaces that fostercreativity. At the firm level, the use of appropriatemetrics motivates such behavior. For example, firmssuch as Motorola and 3M specifically track innova-tions (and sales from those innovations) from prod-ucts that did not exist five years ago. This createsa rejuvenating cycle of innovation that constantlychallenges existing models, modes, and processes.

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However, while these may be effective in generatinginnovations from internal constituents, these effortsmust be combined with external efforts such as build-ing strategic relationships with supply chain partnersin order for a firm to effectively tap supply chain part-ner innovativeness.Product innovation strategy shows a positive effect

on product innovation performance. This result isconsistent with the study of Azadegan and Dooley(2010). The use of new technologies and componentsin product development (product innovation strategy)may offer various options and possibilities of develop-ing novel products and increasing the number of newproducts developed. For example, new technologiescan enable platform products to be built which thenoffer the possibility of building derivative productsbased on the platform product, thus increasing thenumber of new products. Finally, it is important tonote that supply chain partner innovativeness had adirect positive effect on product innovation per-formance (see Figure 2). This suggests that productinnovation strategy represents only one mechanismthrough which supply chain innovativeness affectsinnovation performance in firms. The identification ofa mediating variable (product innovation strategy)that links supply chain partner innovativeness toinnovation performance is a contribution to the litera-ture that has largely focused on the direct linkbetween external sources of innovation and perfor-mance. For example, supplier innovativeness andperformance (Azadegan, 2011; Azadegan & Dooley,2010); outsourcing and operational innovation perfor-mance (Oke & Kach, 2012), and customer innovative-ness and performance (Kodama, 2002; Lau et al.,2010). Indeed, our finding suggests that in additionto innovation strategy, supply chain partner innova-tiveness could lead to other factors includingincreased organizational learning, absorptive capacity,joint product development efforts, innovative processimplementation, and the like, which in turn couldlead to improved product innovation performance.In terms of managerial implications, managers must

recognize the importance of supply chain partnerinnovativeness as a key ingredient in fostering innova-tive capability and strategy. Specifically, our studyshows that it is not sufficient to assume that a focalfirm will enjoy improved innovation performance ifits partners are innovative. What matters are theactions that the focal firm takes as a result of beinginvolved with innovative partners. We show that part-ners’ innovativeness are likely to trigger the focal firmto implement innovation strategies (e.g., to developor use new components in product development)which will in turn lead to improved innovationperformance (novel products). Thus, managers mustrecognize the potential added benefits of supply chain

partner innovativeness and must put mechanisms inplace to implement specific product innovation strate-gies (e.g., the use of new components, materials, andtechnologies in product development) to exploit part-ners’ innovative capabilities. Another important impli-cation of our study is that while it is important tobuild a culture and a climate that supports innova-tion internally, managers must invest in strategicrelationships with supply chain partners because suchinvestments help firms to better tap partners’ innova-tiveness. These relationships, combined with internalinnovation climate, help to effectively tap and utilizepartners’ innovative knowledge. Thus, organizationalprocesses and structures that facilitate the develop-ment of such relationships are encouraged.

LIMITATIONS AND FUTURE RESEARCHWe offer several suggestions to expand upon this

study. First, it could be argued that our innovativenessmeasure (supply chain partner’s innovativeness) whichcaptures the entirety of the relationships, a firm pos-sesses with its supply chain partners, is a limitation ofthe study. We specifically asked the respondents tofocus on the firm’s most valuable supply chain partner(i.e., the buyer or supplier with whom the firm con-ducts maximum business in dollar terms). In line withFrohlich and Westbrook (2001), our intention was toincrease variance and widen the scope of these rela-tionships, unlike previous studies that focus specificallyon either supplier innovativeness or customer innova-tiveness. Indeed, we were not interested in the specificsource of innovation but whether an external source ofinnovation triggers innovation activities within thefirm that lead to innovation performance in the firms.Nevertheless, future studies can separate these supplychain partners between upstream (suppliers) anddownstream (customers) to gain deeper insights.Second, our findings are admittedly limited as the

information is exclusively based on the focal firms’(manufacturers’) perspectives, and we relied on singlerespondents in each manufacturing firm. Future stud-ies might expand this study (albeit in a methodologi-cally challenging fashion) using triadic data whichincludes a supplier, the focal firm, and a customer.Third, future studies can also improve the quality ofthe data by incorporating secondary data rather thanperceptual data. Data on other control variables suchas the level of R&D expenditure and industry sectorshould be collected in future studies to investigate theeffect of these constructs on the variables examinedin this study. Also, new contextual variables likethe stage in the product life cycle, research anddevelopment expenditure, and country of origin (ofsupply chain partners) effects on the innovation chainrelationships can be examined.

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Adegoke Oke (Ph.D., Cranfield University) is anassociate professor of supply chain management inthe Department of Supply Chain Management at theW. P. Carey School of Business, Arizona State Univer-sity in Tempe, Arizona. His current research interestsinclude innovation management in horizontal net-works, supply chains and supply networks, the relativeeffectiveness of different open innovation strategies,and risk management strategies in supply chains. Dr.Oke’s work has been published in the Journal of Orga-nizational Behavior and the Supply Chain ManagementReview, among other outlets, and he received the 2007

Best Reviewer Award from the Journal of OperationsManagement.

Daniel I. Prajogo (Ph.D., Monash University) is anassociate professor in the Department of Managementat Monash University in Victoria, Australia. Hisresearch focuses primarily on operations and supplychain management, quality management and innova-tion management. Currently, Dr. Prajogo’s workexamines inter-firm collaborative innovations withinsupply chain networks. He also is building researchcollaborations with industry partners in Australia.Among the publications in which his articles haveappeared are the International Journal of Operations &Production Management, the International Journal of Pro-duction Research, the International Journal of ProductionEconomics, Supply Chain Management: InternationalJournal, the European Journal of Operational Research,Technovation, R&D Management, the Journal of SmallBusiness Management, and the Journal of Cleaner Pro-duction.

Jayanth Jayaram (Ph.D. Michigan State University)is a professor of management science, and a MooreResearch Fellow, in the Department of ManagementScience of the Moore School of Business at theUniversity of South Carolina in Columbia, SouthCarolina. His research interests are in the areas ofsustainability, supply chain integration, new productdevelopment, performance measurement and strategicpurchasing. Currently, he is working on projectsrelated to sustainability. Dr. Jayaram currently is serv-ing, or has served, as an Associate Editor for the Jour-nal of Operations Management, Decision Sciences, theJournal of Supply Chain Management, and the Journal ofBusiness Logistics. He also serves as an editorial boardmember for IEEE Transactions on Engineering Manage-ment and the Journal of Integrated Supply Management.

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