international e-tail.pdf

Retail e-commerce (e-tail) continues to be anincreasingly important channel for consumer pur-chases around the world. In 2008, e-tail sales

reached $133.6 billion in the United States and $116.6billion in the United Kingdom (e-Marketer 2008a; U.S.Census 2009). European e-tailing was expected to reach€124.1 billion in 2008 (Jongen 2008). In the Asia-Pacific region, e-tail sales reached $73.3 billion in 2007(e-Marketer 2008b). The global proliferation of e-tailing

is being fueled by not merely online-only firms such asAmazon.com (often referred to as pure-play onlineretailers) but also traditional bricks-and-mortar compa-nies. For example, Tesco, the fourth largest retailer inthe world, indicated that home shopping over the Inter-net is an important growth market (Jones 2001). Theretailer monitors and analyzes online competitors’strategies in both its home market (the United Kingdom)and foreign markets to determine when and how toestablish e-tail presences most effectively. Tesco’s effortsto understand customers, competitors, and foreign mar-kets have facilitated effective e-tail strategies in variousEuropean and Asian markets.

Drivers of International E-Tail Performance: The Complexities of Orientations and ResourcesDeborah A. Colton, Martin S. Roth, and William O. Bearden

ABSTRACTRetail e-commerce (e-tail) continues to grow as an important channel of distribution in the global business environ-ment. In this article, the authors present and test a conceptual model of the relationships among firm orientations,strategic resources, and international e-tail performance. Specifically, they investigate the ability of important e-tail firmresources—brand strength and supplier relations—to mediate the effects of market orientation, entrepreneurial orienta-tion, and foreign market orientation on revenue growth and firm performance relative to objectives. Using surveyresponses from a cross-national sample of 174 marketing and e-commerce decision makers, the authors find supportfor the role of brand strength and supplier relations as mediators between market and foreign market orientations andfirm performance. The study provides managerial insights into the types of orientations and resources that can helpdrive e-tail performance and contributions regarding the indirect effects of orientations on international marketing performance.

Keywords: e-tail, resources, orientations, strategy, performance

Journal of International Marketing

©2010, American Marketing Association

Vol. 18, No. 1, 2010, pp. 1–22

ISSN 1069-0031X (print) 1547-7215 (electronic)

Drivers of International E–Tail Performance 1

Deborah A. Colton is Assistant Professor of Marketing andInternational Business, Department of Management and Mar-keting, E. Philip Saunders College of Business, RochesterInstitute of Technology (e-mail: [email protected]).

Martin S. Roth is a professor, Sonoco International BusinessDepartment (e-mail: [email protected]), and William O.Bearden is Bank of America Chaired Professor of Marketing(e-mail: [email protected]), Moore School of Business,University of South Carolina.

2 Journal of International Marketing

Prior research has shown that certain strategic resourcesare critical to e-tail success. Specifically, brand strengthand supplier relations represent organizational resourcesthat drive e-tail competitive advantage. Online retailersbenefit from strong brands (Danaher, Wilson, and Davis2003; Davis, Buchanan-Oliver, and Brodie 2000; Math-wick, Malhotra, and Rigdon 2001) in that consumersuse brands as extrinsic cues of e-tailers’ offerings (Grif-fith and Gray 2002). Strong brands pull online shoppersto retail Web sites and help generate customer satisfac-tion and e-tail loyalty. Successful e-commerce alsorequires quick and accurate order fulfillment (Wolfin-barger and Gilly 2003), necessitating that e-tailers workclosely with their suppliers on product availability, orderprocessing, transportation, and other logistics issues(Korper and Ellis 2001; Lancioni, Smith, and Olivia2000). Strong supplier relations are critical for enablinge-tailers to deliver superior service. The challenge for e-tailers is how to foster and leverage these intangibleand durable strategic resources. That is, what firm capa-bilities can e-tailers use to develop strong brands andeffective supplier relations?

In this article, we present and test a conceptual model ofthe relationships among firm orientations, strategicresources, and international e-tail performance. In doingso, we make the following contributions to the inter-national marketing literature. First, we identify threefirm capabilities that affect e-tailers’ ability to createstrong brands and effective supplier relations: the firms’market orientation, entrepreneurial orientation, andforeign market orientation. Furthermore, we proposethat the effects of these orientations on performance arenot direct but rather are mediated by brand strength andsupplier relations resources. Second, we examine theoutcome of the relationship between orientations andresources in terms of financial performance. Specifically,we study orientation and resource effects on e-tail reve-nue growth as well as performance relative to objectives.As such, we assess e-tail performance beyond commonlyused Web-based research metrics, such as number of hitsor unique page views. Third, this research examinesthese effects on performance across e-tailers competingin international markets. Despite the global nature of e-tailing, most studies on the drivers of online retail suc-cess focus on single countries. Our model incorporates aglobal view of e-tail firm capabilities, and our empiricalwork includes data from e-tailers operating across inter-national markets. Together, these contributions empha-size the importance of understanding not only theresources that are important to performance but also theorientations that are likely to underlie those resources.

Although research has shown the importance of strongbrands and relations with suppliers, this study demon-strates how firms can augment their stock of resourcesby developing market, entrepreneurial, and foreign mar-ket orientations.

Our model of strategic resources, firm orientations, and their effects on the performance of international e-tailers is theoretically grounded in resource-advantage(R-A) theory and the resource-based view (RBV) of thefirm. We proceed by presenting a conceptual model thatdescribes how e-tailer resources mediate the relation-ships between orientation capabilities and performanceand by developing hypotheses. Then, we describe theresearch methods, including our use of survey data froma cross-national sample of marketing and e-commercedecision makers and structural equation procedures forhypothesis testing. Next, we present our results. Weconclude with a discussion of the implications and direc-tions for further research.

CONCEPTUAL FRAMEWORK

Resource-advantage theory (Hunt and Morgan 1995)and the RBV of the firm (Barney 1991; Wernerfelt 1984)provide a framework through which to assess how e-tailers can achieve competitive advantage and superiorperformance. Typically, firms that achieve superior per-formance possess and leverage important resources suchas assets, knowledge, and processes that enable them todevelop and implement successful strategies efficientlyand effectively. These strategies form the basis ofcompetitive advantage, and the more resistant theresources are to duplication or imitation, the more sus-tainable the advantage and superior performance are.As Day (1994), Hult and Ketchen (2001), Wilson andAmine (2009), and others describe, firms often use critical capabilities that independently and collectivelycontribute to the creation of unique resources. Thus,competitive advantage and subsequent performance arecontingent on firms managing capabilities to createvaluable and inimitable resources. These resources canbe leveraged for competitive advantage, leading to supe-rior financial performance (Hunt and Morgan 1995).

Following Hult and Ketchen’s (2001) approach, weidentify certain capabilities that can contribute to e-tailers’ abilities to create valuable resources. Critical e-tail resources are brand strength (Danaher, Wilson,and Davis 2003; Davis, Buchanan-Oliver, and Brodie2000; Griffith and Gray 2002) and supplier relations


(Gregory, Karavdic, and Zou 2007; Korper and Ellis2001; Lancioni, Smith, and Olivia 2000; Rugman, Li,and Oh 2009). The capabilities include the firms’ mar-ket orientation, entrepreneurial orientation, and foreignmarket orientation. Market orientation is the set of pro-cesses and activities used to understand customer needsto satisfy customers (Deshpandé and Farley 1996).Entrepreneurial orientation is a firm’s inclination to takerisks, favor change and innovation, and compete aggres-sively (Miller and Friesen 1982). Foreign market orien-tation refers to an organization’s knowledge about for-eign markets (Simonin 1997). We define brand strengthas the extent to which customers are aware of and rec-ognize brands and view them favorably (Keller 1993),and we define supplier relations as the communicationand coordination between the e-tailer and its primarysupplier (Anderson and Narus 1990).

Firm orientations and resources affect performance(Hunt and Morgan 1995; Lumpkin and Dess 1996).Similar to Noble, Sinha, and Kumar (2002), wehypothesize that the impact of orientations on perform-ance is not direct but rather is mediated by the resourcesthey help create. Much of the extant research on e-tailperformance uses metrics associated with Web site hitsor number of unique visitors, which do not necessarilycorrespond with ultimate financial success. Followingrecent studies that assess effects on performance in thee-commerce and global marketing contexts (e.g., Avloni-tis and Karayanni 2000; Hewett, Roth, and Roth 2003),we use financial measures of performance. Consistentwith Hult and colleagues (2008), we measure financialperformance in multiple ways, in terms of both revenuegrowth and an overall index of performance objectiveachievement. While the former captures an explicit per-centage rate, the latter pertains to how well the e-tailermet objectives relative to online sales, profitability, market share, sales growth, and the number of new customers.

Evidence of the direct effects of market orientation onperformance has been mixed, apparently dependent onthe research context (Kirca, Jayachandran, and Bearden2005). For example, studies in international settingshave found inconsistent direct effects between marketorientation and performance. Yet one of the advantagesof e-tail stores is their ability to serve customers regard-less of their geographic location. Thus, we propose thatmarket orientation (as well as entrepreneurial and for-eign market orientations as described in the next sec-tion) has a first-order effect (e.g., Hult and Ketchen2001) on strategic resources, which in turn affect e-tail

firm performance. This mediated view (Baron and Ken-ney 1986) of the market orientation–performance rela-tionship also builds on the work of Noble, Sinha, andKumar (2002), who advocate a broader perspectivewhen considering the relationship between strategic ori-entations and performance. Thus, our model exploreshow e-tailer resources mediate the relationships betweenorientation capabilities and performance. Figure 1 sum-marizes the constructs and relationships that ourresearch investigates regarding global e-tail perform-ance. We propose and test for mediating effects, andthen we hypothesize specific relationships between ori-entations and resources and between resources and per-formance.

HYPOTHESESOrientation Effects on Resources

Market Orientation. Market orientation is the set ofcross-functional processes and activities directed at cre-ating customer value (Deshpandé and Farley 1996;Kohli and Jaworksi 1990; Narver and Slater 1990). TheInternet is an information-rich medium that enablescompanies to track customers, their purchase histories,and preferences more easily than in traditional markets(Reichheld and Schefter 2000); therefore, e-tailers havemuch to gain by being market oriented.

The more market oriented a firm is, the more it isfocused on processes for creating customer value. Oneof the central marketing activities for creating and cap-turing customer value is the development and marketingof strong brands. Brands are complex resources thatencompass product, organization, person, and symboliccomponents (Aaker and Joachimsthaler 2000), thusrequiring concerted efforts at understanding customerneeds, competitive dynamics, and other dimensions ofmarket orientation.

In addition, part of an effective market orientation isdetermining which products and services to bring tomarket. For most retailers, the products they offer cus-tomers are sourced from suppliers. Thus, creating cus-tomer value requires both sourcing products and devel-oping attractive service offerings. The more orientede-tailers are to customers and competitive offerings, themore effectively they can identify and select key suppli-ers. Furthermore, firms that are highly focused on themarketplace will be more likely to extend this focus totheir channel partners, engaging in more open dialogueand collaborative efforts with their suppliers. In doing


so, the e-tailer and its suppliers can work together inmutually beneficial ways that enhance each other’s businesses.

In summary, a firm’s market orientation can enhance itsability to create strong brands and build supplier rela-tions. Therefore, we expect the following:

H1: The stronger the market orientation, thegreater is the effect on (a) brand strength and(b) supplier relations.

Entrepreneurial Orientation. Entrepreneurial orienta-tion is the set of processes managers use to stimulateinnovativeness, risk taking, and proactiveness (Lumpkinand Dess 1996; Matsuno, Mentzer, and Özsomer 2002;Miller and Friesen 1982). E-commerce and Internetshopping have revolutionized how companies distributeinformation as well as products to consumers. BothInternet start-ups and online stores of traditional bricks-and-mortar firms have continually innovated andaggressively experimented with new ways of attractingand satisfying customers. Thus, an entrepreneurial ori-

entation can be an important asset for firms competingin the e-tail environment.

Conceptually, entrepreneurship (entrepreneurship,entrepreneurial proclivity, and entrepreneurial orienta-tion are commonly labeled constructs that capture theprocesses underlying innovativeness, risk taking, andproactiveness) has been described as an antecedent ofmarket orientation (Deshpandé, Farley, and Webster1993; Grinstein 2008) as well as a common first-orderfactor with market orientation (Hult and Ketchen2001). We adopt the latter approach in our study of e-tail strategy, following Slater and Narver’s (1994) andBecherer and Maurer’s (1997) recommendation that thecomplementary nature of constructs suggests that theybe examined together. Therefore, we examine the extentto which the various firm orientations are related tobrand strength and supplier relations resources.

The Internet represents a fast-paced environment, one inwhich firms can quickly change the online store to becurrent, fresh, and novel. Strong e-tail brands must con-vey these benefits to shoppers. The virtues of an entre-

Figure 1. E-Tailing Orientations, Resources, and Performance

Market orientation H1a

H1b

H2a

H2b

H3a

H3b

H4a

H4b

H5a

H5b

Performance relative to objectives

Revenuegrowth

Brand strength

Supplier relations

Entrepreneurial orientation

Foreign market orientation


preneurial orientation lend themselves to creating andmaintaining an innovative brand presence on the Web.Firms that are proactive, innovative, and willing to takerisks should be able to continually update and refreshtheir brands and the related associations consumershave with their online stores. In contrast, firms that areless entrepreneurial risk having dated sites and brandimagery as a result of their lack of processes for beinginnovative and proactive. Thus, entrepreneurial orienta-tion should be positively related to e-tail brand strength.

Another dimension of effective e-commerce is the firm’sability to make sought-after goods available on demandto customers. Without the burden of physical goodsinventory, e-tail stores can promote a wide assortmentof products and fulfill orders only for those goodsordered by their customers (Levy and Grewal 2000).Success, however, requires strong supplier relations inboth determining the goods most likely to appeal to cus-tomers and ensuring adequate access and delivery ofthose goods after ordered. An entrepreneurial orienta-tion, in which the e-tailer is proactive, innovative, andrisk taking, will enable the e-tailer to communicate andwork effectively with suppliers in assessing the latter’sproduct portfolio and determining the right mix ofproducts and promotions to appeal to online shoppers.Being entrepreneurial also makes firms more willing toengage in partnering and to seek out those with comple-mentary assets (in this case, products) with whom theycan engage (Read et al. 2009). E-tailers lacking in entre-preneurial orientation will be less engaged with out-siders, communicate less, and be more resistant tochange, to the detriment of their relationships with keysuppliers.

In summary, we propose that e-tailers’ entrepreneurialorientation is positively related to brand strength andsupplier relations. Thus, we hypothesize the following:

H2: The stronger the entrepreneurial orientation,the greater is the effect on (a) brand strengthand (b) supplier relations.

Foreign Market Orientation. Foreign market orienta-tion involves the processes needed to acquire knowledgeand experience that are specific to individual countrymarkets. This knowledge pertains to the country’s language, culture, politics, society, and economy(Inkpen and Beamish 1997; Lord and Ranft 2000). Animportant characteristic of online stores is their abilityto reach and serve customers around the world. Websites can be accessed by most computers connected to

the Internet, thus making e-commerce inherently inter-national (Kobrin 2001). Furthermore, compared withthe cost and maintenance of conventional bricks-and-mortar stores, for an international Web presence, glob-alization costs are miniscule (Lynch and Beck 2001;Quelch and Klein 1996). Despite fraud risks, logisticand tax issues, and other barriers to international trade,a recent survey of medium-sized and large online mer-chants showed that close to two-thirds accept overseasorders (Cybersource Corporation 2004).

Doing business internationally has many challenges,including high levels of uncertainty, relational difficul-ties, and product and process adaptation (what Zaheer[1995] labels “liabilities of foreignness”). At the root ofmany of these challenges is a firm’s lack of local marketknowledge (Lord and Ranft 2000). The more resourcesthe firm devotes to acquiring local market knowledge,the less likely it will be to incur these liabilities. Withgreater local knowledge, e-tailers can better understandhow to manage their brands in and across national mar-kets, as well as how to work with key suppliers to servecustomers around the world. Thus, a firm’s orientationtoward foreign markets relative to its internationalknowledge and experience can help the e-tailer buildstronger brands and foster enhanced supplier relations.More formally, we hypothesize the following:

H3: The stronger the foreign market orientation,the greater is the effect on (a) brand strengthand (b) supplier relations.

Resource Effects on Performance

A central tenet of R-A and RBV theories is thatresources can be leveraged for competitive advantage.Such advantage leads to superior firm perform-ance (Barney 1991; Hunt and Morgan 1995). Next, we described how brand strength and supplier relationsresources can be valuable, rare, imperfectly imitable, and nonsubstitutable, thereby enhancing firm performance.

Brand Strength. Two key sources of customer valuecreation and competitive advantage in e-tailing arebrand strength and supplier relations. It is widely recog-nized that brands are one of the most valuable assetsfirms own (Aaker 1991; Lehman, Keller, and Farley2008) For example, an executive at Coca-Colaexplained that it would be more difficult to recover fromdeleting the Coca-Cola brand name and its associationsfrom consumers’ memories than from loss of its physi-


cal assets (Dawar 1998). For a resource to be valuable,it must enable the firm to exploit opportunities or neu-tralize threats (Barney 1991). Some examples of howfirms can use brand strength to exploit opportunitiesinclude leveraging a brand name in new markets orchannels and extending a brand name to a new product,category, or channel. Firms can also use brands to neu-tralize threats, such as defending against competitiveattacks.

Brand strength embodies a set of associations that exist-ing and potential customers perceive a brand as having.The multidimensionality of brand strength enables firmsto implement value-creating strategies that are notsimultaneously being implemented by competitors.Thus, brands that have greater awareness and recogni-tion or that customers view more favorably representvaluable resources that are not shared or matched bycompetitors. Even if resources are valuable and rare,they might not lead to a performance advantage if otherfirms are able to acquire them. In other words, aresource also must be imperfectly imitable (Barney1991). A resource can be imperfectly imitable for dif-ferent reasons, including the following: The resource is dependent on unique historical conditions, the linkbetween the resource and the competitive advantage is causally ambiguous, or the resource is socially com-plex (Barney 1991). As Aaker and Joachimsthaler(2000) describe, brands are complex resources that are organized around four dimensions—namely, the brand as a product (e.g., quality, attributes), anorganization (e.g., organization attributes), a person(e.g., customer–brand relationships), and a symbol (e.g.,visual image, heritage). Thus, the various components of brand strength are linked to the social complexity ofthe firm.

A final requirement for a resource to generate perform-ance advantage is that there must not be strategicallyequivalent or substitutable resources (Barney 1991).Strategically equivalent resources are those that enablecompeting firms to formulate and implement the samestrategies but in different ways. This requirement per-tains to the absence of substitutability. However, asexplained previously, brand strength is multidimen-sional and developed from socially complex links. Otherresources are unlikely to individually or collectivelyreplicate these complexities, nor can they facilitate thesame psychological and emotional impressions as dostrong brands. In summary, strong brands can meet therequirements of being a potential source of a perform-ance advantage.

Although price is a key driver of e-commerce transac-tions, retailer name and reputation are important crite-ria in e-tailer selection (Shop.org and Forrester Research2009). The strength of consumers’ associations with abrand, including perceived functional, social, and self-expressive benefits (Keller 1993; Park, Jaworski, andMacInnis 1986), create one of the most valuable assetsa firm can own (Aaker 1991), including those in theretailing industry (Ailawadi and Keller 2004). Brandloyalty in e-tailing translates into market share gains,showing that stronger brands perform better online thanweaker brands (Danaher, Wilson, and Davis 2003,Degeratu, Rangaswamy, and Wu 2000). Thus, creatingand leveraging a strong brand can be a strategic assetand competitive advantage for online retailers. More-over, branding is acutely important as a perceptual cuebecause the online environment lacks much of the physi-cal interaction between customer and retailer in tradi-tional bricks-and-mortar stores that shape brand asso-ciations (Davis, Buchanan-Oliver, and Brodie 2000;Griffith and Gray 2002). Effective branding can helpcreate experiential value that may otherwise be lackingin the Internet shopping environment (Mathwick, Mal-hotra, and Rigdon 2001).

When consumers encounter strong brands, they mayhave more favorable meanings and associations thanweaker brands (Okazaki 2005). The Web can have amajor impact on brand building and perceptions (Aakerand Joachimsthaler 2000). From an international per-spective, many e-tailers incorporate features on theirWeb sites that contribute to a uniform global image inan effort to enhance brand awareness, recognition, andpositive associations (Okazaki 2005). Retailers benefitfrom strong brands (Ailawadi and Keller 2004), includ-ing those that operate online (Danaher, Wilson, andDavis 2003; Davis, Buchanan-Oliver, and Brodie 2000;Mathwick, Malhotra, and Rigdon 2001). Consumersuse brands as extrinsic cues of e-tailers’ offerings (Grif-fith and Gray 2002). Strong brands can attract cus-tomers to Web sites and facilitate greater e-tail loyalty,thereby enhancing financial performance. Thus, wehypothesize the following:

H4: The stronger the brand strength, the greater isthe effect on (a) performance relative to objec-tives and (b) revenue growth.

Supplier Relations. Although the store’s brand nameand reputation may draw customers to the online store,product availability and prompt delivery are also requi-site conditions for consummating online transactions


(Korper and Ellis 2001; Lancioni, Smith, and Oliva2000). E-tailers must work closely with their supplierson product availability, order processing, transporta-tion, and other logistics issues, making supplier relationsa second source of performance advantage, so long asthese relations are valuable, rare, imperfectly imitable,and nonsubstitutable. Olavarrieta and Ellinger (1997)describe how supplier relations can be valuable assets ifthey enhance efficiency or effectiveness and enable afirm to exploit opportunities or neutralize threats. Forexample, e-tailers can focus on quick and efficient con-sumer response when supplier relations facilitate rapidand efficient product selection and fulfillment. Relation-ships with suppliers involve a complex mix of physical,human, and organizational capabilities, which are notobvious and require time to develop and integrate(Olavarrieta and Ellinger 1997). For example, Wal-Mart’s distribution, by considerably reducing costs, hasenabled it to enter markets once deemed unprofitable.Wal-Mart is able to reduce costs and manage inventorythrough strong relationships with its key suppliers, asevidenced by many suppliers having dedicated officesnear Wal-Mart’s headquarters. Wal-Mart and its com-petitors carry similar product offerings, but its supplierrelations, which are based on effective and efficient dis-tribution, strengthen its market leader position (Olavar-rieta and Ellinger 1997).

To be a source of a competitive advantage, supplier relations also must be imperfectly imitable. Althoughrelationships with suppliers are tied to the unique histo-ries of their companies, they are more likely to be imper-fectly imitable because they are socially complex.Finally, for supplier relations to be a source of advan-tage, they must be nonsubstitutable. Possible substitutesfor strong relationships with suppliers are not clearlyevident. Although conceptually an e-tailer could verti-cally integrate to produce the goods it sells, doing so isusually unfeasible because of the significant resourcerequirements (e.g., manufacturing, materials, labor,inventory). Although competitors might try to replicaterelationships with suppliers, it is unlikely that theseactions will lead to the same strategies and outcomes.

Accurate fulfillment (what is displayed and describedonline matches the order) and reliability (delivery of theright product within the time frame promised) are keydeterminants of consumer e-tail satisfaction and qualityperceptions (Wolfinbarger and Gilly 2003). E-tailers canoffer such services best to customers through effectivesupply-chain management. Vendor-to-retailer linkagesin the supply chain (e.g., order processing, inventory

management, logistics) can facilitate retailer-to-customer links, such as merchandise processing, fulfill-ment, and delivery (Levy and Grewal 2000). By manag-ing their relationships with key suppliers, e-tailers canensure that their customers receive high-quality productselection and provision. Therefore, for e-tailers, brandstrength and supplier relations represent organizationalresources that can lead to competitive advantage basedon increased site traffic and superior service, which sub-sequently lead to superior performance (Day 1994).Such a focus on strategic resources is commensuratewith the R-A and RBV theories, which posit that uniqueassets, such as strong brands and supplier relations, aredifficult for competitors to replicate and thus help dif-ferentiate their possessors (Barney 1991; Hunt andMorgan 1995).

Distribution systems can be valuable resources that cancontribute to superior service delivery (Bowersox,Mentzer, and Speh 1995; Olavarrieta and Ellinger1997). E-commerce involves physical distance betweenthe buyer and the supplier, thus making quick and accu-rate goods delivery critically important (Wolfinbargerand Gilly 2003). To do so, e-tailers must work closelywith their suppliers on product availability, order pro-cessing, transportation, and other logistics issues (Gre-gory, Karavdic, and Zou 2007; Korper and Ellis 2001;Lancioni, Smith, and Olivia 2000). Thus, strong sup-plier relations can enable e-tailers to deliver superiorservice, thereby satisfying customers, which in turnleads to superior performance (Heskett et al. 1994).More formally, our fifth hypothesis summarizes thesepredictions:

H5: The stronger the supplier relations, the greateris the effect on (a) performance relative toobjectives and (b) revenue growth.

METHODS

In this section, we present the procedures used to gatherthe data. We first discuss the survey instrument andselection of informants, and then we explain the proce-dures used to assess nonresponse bias. Finally, wedescribe the measures and steps taken in validating themultiple-item scales used in our survey.

Survey Instrument and Sample

The research was conducted using online survey proce-dures. When possible, we operationalized the constructs

of interest using existing measures. We administered thesurvey in English because target respondents were fromEnglish-speaking countries. First, we pretested the sur-vey using the responses of 15 academic experts and mar-keting managers in an effort to assess the clarity ofinstructions and scale items and the ease of use with theonline delivery. Follow-up interviews after survey com-pletion provided comments on the draft questionnairethat were used to make minor modifications, primarilywith regard to question wording and format (e.g., use ofradio buttons versus drop-down menus).

Key informants were marketing or e-commerce decisionmakers responsible for the operations of online retailingand marketing activities. Informants were sought fromfirms headquartered in various countries. To qualify asappropriate study participants, the firms’ Web sitesneeded to allow complete transactions (i.e., both orderand payment) of physical consumer products. Weexcluded digitized delivery services, such as music andnews, because these services do not necessarily involve asupplier in the value chain. Selecting key informants onthe basis of their e-commerce roles, so that they areknowledgeable about the phenomena under study, iscritical in marketing organizational research (Barclay1991; John and Reve 1982). Therefore, the samplingprocedure required the identification of e-commercefirms and respondents with the appropriate e-tailing andmarketing responsibilities.

We developed the sample using the following steps:First, we obtained a database of online U.S. retailersoffering transactions in the following physical productcategories: apparel and accessories, auto and marineaccessories, beauty, computer-related, consumer elec-tronics, garden, gifts, health care, home accessories, jewelry, office, pet-related, specialty occasion, sportinggoods, and toys. We included a range of product cate-gories to enhance the generalizability of the results.1 Thedatabase contained contact information for Internetmanagers, direct marketing managers, and Internet deci-sion makers. Elimination of duplicate entries and thosewith incorrect or no contact information yielded 936U.S. online retailers.

Second, we identified non-U.S. headquartered onlineretailers in the same product categories using Yahooportal country-specific searches. Initial Internet searchesto determine the countries in which the majority ofonline retailers operate Web sites with English textualcontent identified the following countries: Australia,Canada, Ireland, India, New Zealand, Singapore, and

the United Kingdom, in addition to the United States.Multiple searches using variants of the product cate-gories in each Local Yahoo country domain identified617 online retailers from these eight different countriesfor which Internet marketing or e-commerce managercontact information could be obtained. In some cases,the Internet marketing or e-commerce manager waslisted on the company’s Web site. When precise contactinformation was not disclosed, an e-mail was sent or a telephone call was placed requesting the name and contact information of the Internet marketing or e-commerce manager.

We used two contact methods according to the contactinformation acquired. The international sample wascontacted by e-mail because direct postal addresses forthe majority of the targeted decision makers were notavailable. Conversely, the database used for the U.S.sample included specific postal addresses for the deci-sion makers but no e-mail addresses. We attempted tosearch for direct e-mail addresses; however, most werenot publicly available. Therefore, informants from thedatabase sample were contacted by postal mail. Infor-mants from the portal sample were initially contacted bysending direct e-mails to specific people.

Both sets of potential respondents were initially con-tacted within two weeks of each other, receiving anidentical letter inviting them to participate in the study.The letters outlined the nature of the study and empha-sized respondent confidentiality. As an incentive for par-ticipating, respondents were offered a summary reportbased on the study’s findings (see Robertson, Eliashberg,and Rymon 1995). In line with Dillman (1978), follow-up reminder postcards and e-mails were sent to nonre-spondents after two and four weeks of the initial mail-ing. The letters and e-mails contained the link for theonline survey, with each sample being directed to a separate URL. The follow-up e-mails and postcardsincluded two URLs to keep the two samples separate.This process enabled tracking by method of contact.When respondents reached the Web site, the question-naires were identical, including the same questions andformatting. The data from each sample were stored inseparate databases. The data were later merged into onedatabase and coded by collection method to test forsample differences. Informants were asked to base theirresponses on the online portion of their retail operationsif the company operated both online and physical stores.Furthermore, if respondents’ companies operated morethan one e-commerce site, they were asked to focus onthe Web site considered their companies’ primary site.



From the initial combined postal and e-mailing of 1553letters (936 plus 617), 30 were returned as not applica-ble to the firms’ operations. In total, 195 online surveyswere completed (128 from the United States and 67from non-U.S. firms, of which 174 were usable), for aneffective response rate of 12.8%. Response rates weresimilar from both the database and the portal samples(13.8% and 11.2%, respectively). Respondents repre-sented all eight countries and the 15 product categoriesdescribed previously. The average sales in U.S. dollarswere $2.34 million. Respondents averaged more thanfive years of employment with their companies. Theproduct categories most frequently represented arehealth (n = 24), sports (n = 23), and jewelry (n = 22).The results of one-way analyses of variance on eachconstruct showed no significant response differencesbased on product category.

Nonresponse Bias

First, we examined nonresponse bias using the proce-dures that Armstrong and Overton (1977) recommend:We compared the responses from the initial mailing withthose received after the first and second reminder mail-ings for both the database and the portal samples. Inaddition, we compared responses from each of the twosamples. Comparisons were made on all variables in thestudy, including firm characteristics. The results of thesecomparisons showed no significant differences acrossthe waves of responses or between the two samples (allp-values > .10). Second, we collected secondary dataregarding the locations and product categories of nonre-sponding firms. Comparisons of these data with thoseresponding showed no significant differences.

Measurement

We used multi-item measures based on preexistingscales for the majority of variables investigated. TheAppendix summarizes these measures, their originalsource, and response format. In general, the scales usedwere adapted to fit the e-tailing context with only minorphrasing adjustments. We assessed market orientationusing a scale adapted from Deshpandé and Farley’s(1996) condensed market orientation scale, developedfrom a prospective market orientation meta-analysis.This measure included nine items regarding customerand competitive norms in their companies. We usedadaptations of items that Miller and Friesen (1982) andCovin and Slevin (1991) developed to assess entrepre-neurial orientation. This scale comprised seven itemsreflecting the company’s risk inclination, innovativeness,

and proactiveness. We developed a foreign market orientation measure by adapting scales from Simonin(1997) and Lord and Ranft (2000). From the collabora-tive know-how scale (Simonin 1997), we learned thatknow-how must encompass the requisite knowledgespecific to the phenomena under study. Then, from Lordand Ranft’s (2000) transfer of local market knowledgescale, we identified items that pertained to foreign market knowledge. We used four items to measure the degree of foreign market knowledge within the e-commerce operations.

To assess brand strength, we drew on Keller’s (1993)brand equity work, in particular the dimensions relatedto brand knowledge. We generated the initial pool ofitems for brand strength from a review of the literature,other brand-related scales, and consultation with mar-keting professionals. In his conceptualization of brandequity, Keller (1993) outlines dimensions of brandknowledge, including brand awareness and brandimage. Brand image consists of type, favorability,strength, and uniqueness of brand associations, andbrand awareness consists of brand recall and recogni-tion. We used a five-item scale capturing the strength ofthe firm’s online brand relative to that of its competitorsin this study. The first item pertains to the strength ofthe retail brand on the Internet compared with that ofonline competitors. The next three items capture Inter-net retail brand awareness, quality, and favorabilityrelative to other brands in the same retail category. Thefifth item pertains to how strongly the brand is recog-nized with its retail category on the Internet. Weassessed supplier relations using a scale adapted fromGaski and Nevin (1985). We restructured Gaski andNevin’s marketing channel power scale items to a Likert-type format, and we included factors specific toe-tailing that assessed the online retailer’s relationshipwith its primary supplier.

We measured online retail performance in terms ofobjective achievement (Avlonitis and Karayanni2000)—that is, how well the e-tailer performed relativeto the objectives it set for online sales, profitability, mar-ket share, sales growth, and number of new customerobjectives in the most recent annual fiscal period(Hewett and Bearden 2001). In addition, we included ameasure to capture actual percentage change in revenueas an absolute measure of financial performance to com-plement the relative measure of objective achievement ofperformance. Because the performance relative to objec-tives scale and the revenue growth measures were nothighly correlated (r = .16), and consistent with our theo-


retical predictions (i.e., H4 and H5), we inferred thatthese relative and absolute measures are different, andthus we retained both for subsequent analyses. Includ-ing both is also consistent with Hult and colleagues’(2008) prescription to use multiple measures of performance.

We used procedures based on Anderson and Gerbing(1988) and Fornell and Larcker (1981) to assess dis-criminant validity, reliability, and dimensionality for all reflective scales. In addition, because respondentsconsisted of two groups—U.S.-based and non-U.S.-based online retailers—we used multigroup analyses toevaluate measurement invariance, as Steenkamp andBaumgartner (1998) suggest. To check for multi-collinearity, we computed variance inflation factors foreach construct. The variance inflation factors rangedfrom 1.34 for supplier relations to 2.26 for entrepre-neurial orientation. These values are below the suggested value of 10 (Kline 2005), indicating anabsence of multicollinearity. Before measure validation,we analyzed whether the data were appropriate for fac-tor analysis. To determine data appropriateness, weexamined the data using the Kaiser–Meyer–Olkin Mea-sure of Sampling Adequacy (KMO) and Bartlett’s Test ofSphericity (BTS), employing all initial items for each ofthe multi-item scales. The KMO for this study’s data is.832, which is “meritorious” (see Sharma 1996), sug-gesting that the data are appropriate for factor analysis.The BTS for this study resulted in an approximate chi-square of 2786 with 2080 degrees of freedom and a.000 level of significance. Both the KMO and the BTSstatistics indicate that the data were appropriate for factor analysis.

Using exploratory factor analyses, we examined eachmulti-item measure by evaluating the factor structures,loadings, and interitem correlations. To establish theunidimensionality associated with each multi-itemmeasure, we examined scree plots and the number ofcomponents extracted on the basis of the eigenvalue-greater-than-one rule. For each scale, only a single uni-dimensional factor resulted. Moreover, across all thescales, no items had low factor loadings (all λ > .50).The initial factor structure for the market orientationscale resulted in two factors. When we deleted the fifthand ninth items (“We measure customer satisfactioninfrequently” and “Data on customer satisfaction aredissemination at all levels in our e-commerce unit on aregular basis”), a one-factor solution with seven itemsresulted. The factor loadings and the pattern and mag-nitude of the interitem correlations were similar for the

U.S. and international samples. The initial factor struc-ture for the foreign market orientation resulted in onefactor. We retained all four original items measuring for-eign market orientation. For entrepreneurial orienta-tion, the initial structure with all seven items resulted ina two-factor solution. After several iterations, thereduced scale included all but one of the original items(“In general, our e-commerce top managers favor low-risk projects [i.e., project with certain rates of return]”).Loadings for the six-item scale (two items for eachdimension—innovativeness, proactiveness, risk taking)ranged from .522 to .823. In addition, the structure ofthe loadings and interitem correlations were similaracross the different samples (U.S. and international).The factor structure for brand strength (loadings for thefive items ranged from .704 to .890) was similar forboth the U.S. and the international samples. The resultsfrom the exploratory factor analysis for the supplierrelations measure led to a two-factor solution. After wedeleted three items (“Our most important supplier doesnot offer products to end users on their Web site,”“There is an overlap in products offered to end users onour Web site and our most important supplier’s Website” [reverse coded], and “Our most important suppliermakes it difficult for our e-commerce business to do itsjob”), the reduced scale included four items that loadedon a single factor. Again, the Appendix indicates thefinal measurement scales, as well as Cronbach’s alphavalues. All scales had alpha values greater than .77, pro-viding evidence of acceptable reliability (Peter 1979). Ina series of additional exploratory factor analyses, nosubstantial cross-loadings occurred for any of the itemsacross the different constructs. We assessed discriminantvalidity using confirmatory factor analysis to comparethe average variance extracted for each construct inpairs of all possible combinations of constructs with thesquared correlation between the constructs (Fornell andLarcker 1981). As Table 1 shows, the squared phi coef-ficients between each of the pairs of constructs were lessthan the average variance extracted, indicating discrimi-nant validity.

Last, we investigated cross-national measurementinvariance to examine the strength and generalizabilityof scales between the U.S. and non-U.S. respondents.Using Steenkamp and Baumgartner’s (1998) prescribedhierarchical confirmatory factor analysis procedure, weevaluated the multi-item measures for invariance.Specifically, we analyzed data from the U.S. and inter-national samples concurrently to determine the level ofequivalency that existed across the two samples.Steenkamp and Baumgartner suggest testing for invari-


ance cross-culturally. Given the relatively small samplesizes from the individual countries, we assessed invari-ance between the U.S. and international samples. Con-firmatory factor analysis indicated that we achieved par-tial equivalence for the foreign market orientation andsupplier relations scales. Full equivalence was estab-lished for all the remaining scales. On the basis of theseresults, we deemed the scales to be appropriate for useacross the countries included in this study. Although fullequivalence is ideal according to Steenkamp and Baum-gartner, they explain that it is not expected to be real-ized. In addition, they state that full metric equivalenceoften does not hold in practical applications. Thus, thelevel of equivalence obtained in this study seems to beappropriate.

ANALYSIS AND RESULTS

Table 2 shows the summary statistics, variable intercor-relations, and coefficient alpha estimates of reliabilityfor all measures included in the study. Consistent withthe mediation analyses of Andrews and colleagues(2004), we employed structural equation methods intests of the hypotheses. For the six multi-item variables,we used average scores to reflect each of the constructs,with error variance fixed at a level appropriate to itscoefficient alpha reliability (Anderson and Gerbing1988; MacKenzie, Podsakoff, and Ahearne 1998;

Steenkamp, Batra, and Alden 2003). For the single-itemrevenue growth performance measure, we set the itemloading to 1.0 and the error term to .0.

To investigate the relationships among the antecedentfirm orientations, the firm resources, and online retail-

Table 1. Discriminant Validity

Table 2. Means, Standard Deviations, and Correlations Among Constructs

1 2 3 4 5 6

Market orientation .64

Entrepreneurial orientation .23 .50

Foreign market orientation .07 .18 .68

Brand strength .23 .16 .14 .73

Supplier relations .14 .03 .03 .11 .60

Performance relative to objectives .21 .18 .16 .37 .12 .75

Notes: The bold diagonal elements are the average variance extracted for eachconstruct. Off-diagonal elements are the squared correlations between the con-struct pairs.

M SD Items 1 2 3 4 5 6 7

1. Market orientation 5.28 1.23 9 .90

2. Entrepreneurial orientation 4.21 1.21 7 .48 .77

3. Foreign market orientation 3.33 1.79 4 .26 .42 .82

4. Brand strength 4.68 1.39 5 .48 .40 .38 .90

5. Supplier relations 5.04 1.44 7 .38 .17 .18 .33 .84

6. Performance relative to objectives 3.78 1.53 5 .46 .42 .40 .61 .34 .92

7. Revenue growth 51.69 75.28 1 .10 .06 .01 .21 .28 .16 —

Notes: n = 174. Constructs 1–6 are measured using seven-point scales. Construct 7 is measured using percentage; italicized numbers on the diagonals for constructs1–6 are coefficient alpha estimates of internal consistency. All correlations higher than .258 are statistically significant (p < .01).


ing performance, we estimated three path analysis mod-els (Andrews et al. 2004; Baron and Kenney 1986).Table 3 summarizes the results of these model estima-tions. First, we estimated the fully mediated Model 1proposed in Figure 1, in which the two resource factors(i.e., brand strength and supplier relations) mediate theeffects of the antecedent firm orientation variables (i.e.,market orientation, entrepreneurial orientation, andforeign market orientation) on the two performanceoutcomes. We estimated two additional models to deter-mine whether the relationships between the orientationantecedents and the performance outcomes are medi-ated by the resource factors. Second, we estimatedModel 2, which was composed of only the direct effectsof the three antecedent firm orientations on perform-ance relative to objectives and revenue growth. Third,we estimated Model 3 (i.e., the no-mediation model). In this latter analysis, we included the direct effects ofthe antecedents, as well as the effects of the two hypoth-esized mediator resource variables. As Baron and Ken-ney (1986) describe, if full mediation exists, the no-mediation model (Model 3) should not be significantlybetter than the fully mediated model (Model 1).

The first column of Table 3 summarizes the results ofthe hypothesized fully mediated Model 1. In addition,Figure 2 graphically depicts the path coefficients fromModel 1. Overall, the model provides a reasonable fit tothe data. The chi-square fit statistic was 13.79 (p = .09,8 d.f.); the root mean square error of approximation(RMSEA) value was .07. The goodness-of-fit index(GFI), comparative fit index (CFI), and nonnormed fit index (NNFI) statistics were .97, .97, and .93, respectively.

Effects of Orientations on Resources: H1–H3

As summarized by the estimates in the top section of fully mediated Model 1 in Table 3, and as Figure 2graphically depicts, three of the six hypothesized pathcoefficients regarding the effects of the antecedent firmorientation variables on the two firm resource variables(i.e., brand strength and supplier relations) were significant. In support of H1a and H1b, market orienta-tion was positively associated with brand strength (β =.39, p < .01) and supplier relations (β = .45, p < .01), aswe predicted. However, neither path involving entrepre-neurial orientation was significant. Therefore, H2a andH2b were not supported, and the expected influence ofentrepreneurial orientation on brand strength and sup-plier relations was not evident. The results for H3regarding the effects of foreign market orientation were

mixed. Specifically, the hypothesized relationshipbetween foreign market orientation and brand strengthwas positive and significant (β = .28, p < .05), as we pre-dicted and in support of H3a. However, we found nosupport for the predicted positive relationship betweenforeign market orientation and supplier relations (i.e.,H3b).

Effects of Resources on Performance: H4–H5

As summarized by the estimates in the bottom portionof the Model 1 results in Table 3, and as Figure 2 graph-ically depicts, all four of the hypothesized path coeffi-cients regarding the effects of the firm resource variableson the two performance measures (i.e., performancerelative to objective and revenue growth) were signifi-cant. First, the path coefficients between brand strengthand performance relative to objectives and revenuegrowth were .63 (p < .01) and .15 (p < .10), respectively.These results offer strong support for the effects ofbrand strength on the measure of performance relativeto stated objectives (i.e., H4a) and modest support forthe effects of brand strength on the percentage measureof revenue growth (i.e., H4b). Note that this latter rela-tionship is estimated using measures that differ substan-tially in terms of measurement response format. Strongbrands—ones that have superior awareness, recogni-tion, and favorable quality perceptions—are associatedwith better performance.

Second, support for our fifth two-part hypothesis on theeffects of supplier relations on performance was alsorevealed by the fully mediated Model 1 results. In sup-port of H5a and H5b, the path coefficients between firmresource supplier relations and performance relative toobjectives and revenue growth were .18 (p < .05) and.19 (p < .05), respectively. These significant path esti-mates indicate the importance of effective supplier rela-tions on long-term performance outcomes.

Direct and Indirect Effects

In an effort to investigate the direct and indirect (medi-ating) effects of the three antecedent resource variables,we estimated two additional models. Table 3 summa-rizes these results as well. First, in tests of the directeffects Model 2, we estimated only the six pathsbetween the three firm orientation variables (i.e., mar-ket, entrepreneurial, and foreign market orientations)and the two performance measures. The overall fit ofthis simpler conceptualization was unsatisfactory. Thechi-square fit statistic was 64.94 (p < .01, 4 d.f.); the


RMSEA value was .34, and the GFI and CFI statisticswere .84 and .45. None of the paths involving the effectsof the orientation variables on the revenue growthvariable were significant. However, the three pathsinvolving the relationships between market orientation(β = .37, p < .01), entrepreneurial orientation (β = .19,p < .05), and foreign market orientation (β = .28, p <

.01) and performance relative to objectives were significant.

Second, we estimated the no-mediation model (Model3). The third column of Table 3 summarizes theseresults. In this analysis, we included all direct and indi-rect effects. In contrast to the direct effects Model 2

Table 3. Results of Mediation Analysis

χ2 d.f.χ2 d.f. Difference Difference CFI GFI NNFI RMSEA

Model 1: fully mediated 13.79 8 — — .97 .97 .93 .07

Model 2: direct antecedent effects 64.94 4 –51.15 4 .45 .84 –.38 .34

Model 3: no mediation 2.51 2 11.28 6 1.00 .99 .98 .04

Model 1: Model 2: Model 3:Fully Direct Antecedent No

Mediated Effects Mediation

Market orientation–brand strength .39*** .39***

Market orientation–supplier relations .45*** .46***

Entrepreneurial orientation–brand strength .13 .12

Entrepreneurial orientation–supplier relations –.10 –.11

Foreign market orientation–brand strength .28*** .27**

Foreign market orientation–supplier relations .15 .15

Market orientation–performance relative to objectives .37*** .13

Market orientation–revenue growth .10 –.10

Entrepreneurial orientation–performance relative to objectives .19** .11

Entrepreneurial orientation–revenue growth .04 .04

Foreign market orientation–performance relative to objectives .28*** .13

Foreign market orientation–revenue growth –.02 –.13Brand strength–performance relative to objectives .63*** .46***

Brand strength–revenue growth .15* .24**

Supplier relations–performance relative to objectives .18** .12

Supplier relations–revenue growth .19** .24**

R2

Brand strength .40 .38

Supplier relations .21 .21

Performance relative to objectives .50 .29 .53

Revenue growth .07 .01 .09

*p < .10.**p < .05.***p < .01.Notes: Fit difference between Models 1 and 3 is χ2 diff. = 11.28, d.f. difference = 6, p = .08. Standardized path estimates are shown.


results, the overall fit of this more complex model wassatisfactory. Specifically, the chi-square fit statistic was2.51 (p = .28, 2 d.f.); the RMSEA value was .04, and theGFI, NNFI, and CFI statistics were .99, .98, and 1.00,respectively. If full mediation exists, the fit of Model 3(no mediation) should not be significantly better thanthe fit of Model 1 (full mediation), and the direct effectpath estimates in Model 3 associated with theantecedent variables to the dependent variables shouldnot be significant (Andrews et al. 2004, p. 118).

As Table 3 shows, substantial evidence of mediation andthe strong intervening effects associated with brandstrength and supplier relations on performance was pro-vided. The chi-square fit statistic difference betweenModels 1 and 3 was only marginally significant at 11.28(p = .08, 6 d.f.). In addition, none of the direct effectparameter estimates reflecting the relationships betweenthe antecedent firm orientation variables and the twoperformance outcomes were significant. Moreover, allbut one of the original path coefficient results reportedhere in support of the hypotheses and tests of Model 1

remained significant. Overall, then, these results supportthe important role of firm resource factors as mediatorsof the relationships between organizational orientationsof the firm and overall firm performance.

Previous research suggests that drivers of firm perform-ance are consistent cross-nationally (Hult et al. 2007).To examine the cross-national generalizability of ourresults, we conducted moderated regression analyses.First, we examined the extent to which headquarterlocation (U.S. versus non-U.S.) moderated the relation-ship between the orientations (market, entrepreneurial,and foreign market) and resources (brand strength andsupplier relations). We used headquarter locationbecause marketing management practices may differ as a result of national differences in markets, competi-tion, and other aspects of the business environment(Hewett and Bearden 2001; Hewett, Roth, and Roth2003; Roth et al. 2009). The results indicated that head-quarter location did not significantly moderate the orientations–resources relationships (p > .05). Secondwe investigated whether headquarter location moder-

Figure 2. E-Tailing Orientations, Resources, and Performance: Path Analysis Results

*p < .10.**p < .05.***p < .01.Notes: χ2 = 13.79 (8 d.f., p = .087); RMSEA = .07; GFI = .97; CFI = .97; and NNFI = .93.

Market orientation

.39**

.45***

.13

–.10

.28***

.15

.56**

.53**

.63***

.15*

.18**

.19**

Performance relative to objectives

Revenuegrowth

Brand strength

Supplier relations

Entrepreneurial orientation

Foreign market orientation

14

44

44

44

44

44

44

44

44

44

43

14

44

44

44

44

31

44

44

44

44

3

.30**


ated the relationships between the resources and per-formance. These also were not statistically significant,with the exception of the relationship between brandstrength and revenue growth (p < .05). These resultssuggest that the relationships among orientations,resources, and performance are relatively generalizablecross-nationally.

DISCUSSIONImplications

The overall objective of this research was to enhanceunderstanding of the capabilities international e-tailerscan deploy to foster and leverage key strategic resources.We used the R-A and RBV theories to develop a concep-tual model of firm orientations, strategic resources, and financial performance. We analyzed cross-nationaldata from e-tailers; they supported our contention thatthe effects of market orientation and foreign marketknowledge on performance are mediated by e-tailerbrand strength and supplier relations. Thus, thisresearch shows how certain unique resources importantto e-tailing are established and how different types ofcapabilities and resources (i.e., orientations, brandstrength, and supplier relations) are related to oneanother to create competitive advantage.

The implications of this study for e-tail highlight theimportance of understanding customers and markets.Knowledge of customers’ expectations can help facili-tate a competitive advantage. Research has shown theimportance of brands and relationships with suppliersto business success. However, understanding the firmorientations requisite to build strong brands anddevelop supplier relations is not as clear. Specifically, theorganizational culture of an e-tailer manifested in itsmarket and foreign market orientations can facilitate itsstock of unique resources. To strengthen their firm’smarket orientation, international marketers coulddevelop customer-centric processes that include sharinginformation about customers across business functions,communicating with customers, and understanding cus-tomers’ needs. Similarly, firms should apply their knowl-edge of differences between international markets totheir e-commerce strategies. If firms lack foreign marketknowledge or do not consider the different characteris-tics of international markets, they may want to invest instrategies to acquire those skills. Developing a foreignmarket orientation is especially important for firmswanting to attract sales from outside their domesticmarket. A “one-size-fits-all” e-commerce strategy seems

less likely to lead to better performance than strategiesthat consider market differences. A more market-oriented, customer-centric organizational culture willhelp a firm strengthen its brand and relationships withsuppliers by understanding its customers both domesti-cally and internationally.

In addition to developing market and foreign marketorientations, firms should consider investments in otherbrand-building efforts to help position them for betterperformance. The value of developing relationships withsuppliers is another aspect of e-tailing that deserves theattention and effort of managers. Specifically, e-tailmanagers should consider their network of suppliersand focus on ways to strengthen those relationships.Overall, this study illustrates the importance of identify-ing elements of organizational culture that enhance theunderstanding of customers and markets that canstrengthen brands and relationships with suppliers. Furthermore, stronger brands and relationships withsuppliers can lead to a competitive advantage.

This study included a sample of e-tailers from differentcountries and measures adapted to fit e-tailing. Despitethe e-tail focus, the findings might be applicable to otherbusiness contexts and markets because the conceptualframework and hypotheses considered the extant inter-national marketing and strategy literature streams.Firms not in e-tailing that develop the orientations inthis study may find that the strength of their brands andrelationships with suppliers are enhanced. The mediat-ing role of resources may hold under different contextsas well.

These findings support the R-A and RBV theories’ con-tention that competitive advantages can be accruedthrough the development and deployment of unique andinimitable assets (Barney 1991; Hunt and Morgan 1995;Wernerfelt 1984). Furthermore, the study reinforces theimportance of key capabilities, specifically market andforeign knowledge orientations, on resources and ulti-mately performance (Day 1994; Hult and Ketchen2001). Specifically, the results suggest that the impact of orientations on performance was mediated by the resources that the orientations help create. That orientation effects on performance are indirect (see Noble, Sinha, and Kumar 2002) contributes toknowledge of the interrelationships among capabilities,resources, and performance (Kirca, Jayachandran, andBearden 2005). Thus, resources such as brand strengthand supplier relations are critical mediators of the orientation–performance relationship. This study


demonstrates the antecedent nature of market and foreign market orientations to brand strength and sup-plier relations. Identifying other orientations (e.g., strate-gic orientation, technological orientation) that arerelated to brand strength and supplier relations wouldcontribute to both academic research and practitionerunderstanding. Similarly, there may be other resourcesthat mediate the orientations–performance relationships.

Limitations and Further Research

As with any study that assesses effects on business per-formance, there are likely additional measures that mayhelp explain variance in performance. In the e-taildomain, cost to serve the customer, reflecting the totalsupply chain cost from the source to the customer(Laseter, Rabinovich, and Huang 2006), warrants con-sideration for inclusion in further research. The cost ofserving customers varies across product categories. Forexample, the cost of serving luggage customers is muchless than serving shoe customers because of fewer differ-ences in packaging, product life cycles, return rates,inventory requirements, and shipping (Laseter, Rabi-novich, and Huang 2006). Thus, further e-tail researchcould control for cost-to-serve rates when assessing per-formance. The nature of the product is another avenuefor further research. Although the focus of this study wason physical products, future work could consider digitalproducts—such as music, news, e-books, software, andinformation—to determine whether differences existacross product types. Last, this study considered thebrand strength of e-tailers. Specific dimensions of brandstrength warrant consideration. For example, percep-tions of e-tail brand imagery and their fit with the inter-national environments they serve (Roth 1995) wouldprovide insights on leveraging brand strength. Also ofinterest might be the brands of the products that e-tailersoffer. For example, e-tailers often carry products withbrand names that vary in strength. Future studies mightconsider the moderating effects of product-level and e-tailer brand strengths on performance.

This study presented a model of e-tailing within the context of the R-A and RBV theories. The orientations,resources, and performance relationships may be applicable to other types of businesses. Although thesample included e-tailers and the scales were adapted for e-tailing, future studies could consider the orienta-tions and resources and adapt the measures to fit othertypes of business. Research has shown that resources are related to performance. Thus, firms that operate in other markets or industries may find that the

resources identified in this study also mediate the orientations–performance relationships. Future studiesmight consider identifying other resources that are likelyto mediate the relationships as well. Furthermore, exam-ining other orientations would be beneficial from theo-retical and practical perspectives.

Both practitioners and academics have noted the impor-tance of cross-functional input in new product develop-ment and other areas of international marketing efforts.Given that e-tailing involves an online presence built oninformation technology, it too has cross-functionalityaspects to its management and performance. Our sampleincluded responses from both marketing and technologymanagers. Post hoc analysis suggested that though deci-sion makers in marketing and technology generally hadsimilar perceptions of their orientations and resources,they tended to differ on their firms’ brand strength andforeign market orientation. Future studies will continue tobenefit from cross-functional, multisample perspectives.

Caveats are warranted regarding the research methods.The finding that entrepreneurial orientation does nothave a positive association with brand strength or supplier relations may be due to different factors. Themulti-item measure might not have fully captured the entrepreneurial spirit of e-tailers. Given that e-commerce is a relatively young market compared withtraditional markets, there may be other elements thatalso reflect an entrepreneurial orientation. Competingonline is different from competing in long-establishedmarkets. The time frame of market entry is muchshorter than traditional market time frames in whichmany firms may have decades of experience. In addition, initial e-tailing market entry was swift andmassive, implying that many of the firms may have hadsimilar characteristics that reflect new or differentdimensions of entrepreneurial orientation. Future studies should consider how to measure entrepreneurialorientation in early-stage markets.

Although the surveys were conducted among knowl-edgeable e-retailer decision makers, the problems associ-ated with self-reported data from online and mail sur-veys are possible. The study employed perceptualmeasures for all but one of the constructs, and we recog-nize the potential for single-informant response bias.Despite the high internal consistency reliability estimatefor the performance relative to objectives outcome scale,we also acknowledge the formative nature of this meas-ure. In addition, the outcome measures were collectedcontiguously with the other construct indicators. As


such, the potential exists for common methods variance(see Hewett and Bearden 2001). However, analyses ofthe multi-item scales provided supportive evidenceregarding the reliability and discriminant validity of the measures. The correlational nature of the researchdesign also precludes causal assertions regarding the esti-mated relationships. In addition, larger national sampleswould be beneficial for comparing and testing potentialinternational differences using structural equation meth-ods. Last, although eight different countries were repre-sented, the study was restricted to respondents fromEnglish-speaking countries. Further research should con-sider a broader combination of countries and cultures.

APPENDIX: FINAL SCALE ITEMS

Market Orientation (Adapted from Deshpandéand Farley 1996; Cronbach’s α = .90)

Please rate the following questions from a rating of 1 to 7,with 1 as “strongly disagree” and 7 as “strongly agree.”

•Satisfying our customers is our most importantbusiness objective.

•We constantly communicate our commitment toserving customer needs.

•We share information about our successful andunsuccessful experiences across all business functions.

•Our strategy for competitive advantage is basedon our understanding of customers’ needs.

•We have regular performance measures of cus-tomer service.

•Our competitors are more customer focused thanwe are. (reverse coded)

•I believe that our business exists primarily toserve customers.

Entrepreneurial Orientation (Adapted fromCovin and Slevin 1991; Miller and Friesen1982; Cronbach’s α = .77)

Please rate the following questions from a rating of 1 to 7,with 1 as “strongly disagree” and 7 as “strongly agree.”

•In general, our e-commerce top managers favor astrong emphasis on marketing tried and trueproducts. (reverse coded)

•In the past year, my firm has marketed many newlines of products on the Web site.

•In dealing with competitors, our e-commerceapproach is to respond to actions which competi-tors initiate. (reverse coded)

•In dealing with competitors, our e-commerceapproach is to pursue and aggressive, competitiveposture.

•In general, our e-commerce top managers believethat bold, wide-ranging acts are necessary toachieve the firm’s objectives.

•When confronted with decision-making situa-tions involving uncertainty, our e-commerceapproach is to adopt a cautious, “wait-and-see”posture. (reverse coded)

Foreign Market Orientation (Adapted fromLord and Ranft 2000; Simonin 1997; Cronbach’s α = .82)

Please focus on your primary e-commerce operations.Please rate the following questions from a rating of 1 to 7,with 1 as “strongly disagree” and 7 as “strongly agree.”

•Before we started our primary Web site, somepeople in my company had experience in inter-national markets.

•My company knows how to market products inother countries.

•Few people in my company’s primary Web siteoperations are knowledgeable about foreign mar-kets. (reverse coded)

•Our e-commerce strategy considers differencesbetween the home market and foreign markets.

Brand Strength (Cronbach’s α = .90)

Please consider your primary e-commerce Web site andthe retail category you selected. Please rate the followingquestions from a rating of 1 to 7, with 1 as “the weak-est” and 7 as “the strongest.”

•Compared to your online competitors, howwould you rate the strength of your company’sretail brand on the Internet?

•Overall, compared to other brands in your retailcategory, how would you rate the level of aware-ness of your retail brand name on the Internet?


•Overall, compared to other brands in your retailcategory, how would you rate the level of qualityassociated with your retail brand name on theInternet?

•Overall, compared to other brands in your retailcategory, how would you rate the level of favora-bility associated with your retail brand name onthe Internet?

•Overall, please rate the level to which your brandis recognized with its retail category on the Internet.

Supplier Relations (Adapted from Gaski andNevin 1985; Cronbach’s α = .84)

Considering the relationship with your most importantsupplier with which you are familiar, please indicateyour level of agreement with each of the following state-ments on a scale of 1 to 7, with 1 as “strongly disagree”and 7 as “strongly agree.”

•There is open communication between our e-commerce business and our most importantsupplier.

•Our e-commerce business and our most impor-tant supplier share common objectives.

•Our most important supplier does not like manyof the things our e-commerce business does.(reverse coded)

•The products we get from our most important sup-plier can also be purchased by end-users on ourmost important supplier’s Web site. (reverse coded)

Performance Relative to Objectives (Adaptedfrom Avlonitis and Karayanni 2000; Cron-bach’s α = .92)

Please indicate the extent to which your company’s Website has achieved the following outcomes relative to itsoriginal objectives for the most recent annual fiscalperiod. Please rate the following questions from a ratingof 1 to 7, with 1 as “well below objectives” and 7 as“well above objectives.”

•Total sales

•Profitability

•Market share

•Sales growth

•Number of new customers

NOTE

1. We excluded certain product categories for the fol-lowing reasons: food because it is perishable; digitalproducts because they are delivered electronically;pharmaceuticals because a prescription is required;consumer durables and large-ticket home repairproducts because delivery costs are substantiallyhigher than for other consumer products; and indus-trial products because our focus is on e-tailing, whichdoes not include business-to-business marketing.

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THE AUTHORS

Deborah A. Colton is Assistant Professor of Marketingand International Business in the E. Philip Saunders Col-lege of Business at the Rochester Institute of Technology.Her research interests combine Internet marketing andglobal marketing with an emphasis on cross-nationalstudies of e-commerce, branding, and corporate blog-ging. Her research has been published in Journal ofInternational Marketing and Journal of World Business.She teaches Internet Marketing, Global Marketing, andMarketing Concepts at both the graduate and theundergraduate levels. In addition, she teaches the onlineprogram at Rochester Institute of Technology. Shereceived her doctoral degree in International Businesswith a concentration in Marketing from the Universityof South Carolina in 2004.

Martin S. Roth is a Professor in the Sonoco Inter-national Business Department, Moore School of Busi-ness, University of South Carolina. His areas of expert-ise include global corporate and marketing strategy. His research has been published in leading journals,including Journal of Marketing Research, Journal ofInternational Business Studies, Journal of ConsumerResearch, Journal of International Marketing, andmany others. He currently serves on the editorial review


boards of Journal of International Business Studies,Journal of Advertising, Journal of World Business, andJournal of Public Policy & Marketing. He has receivedundergraduate and graduate teaching awards at Univer-sity of South Carolina. Before joining the Moore School,he held faculty positions in the Carroll School of Man-agement at Boston College and has also taught at theKatz Graduate School of Business (University of Pitts-burgh), the Arthur D. Little School of Management(Boston), and at universities in Austria, France, HongKong, and Thailand.

William O. Bearden is Bank of America Chaired Profes-sor of Marketing at the University of South Carolina.His areas of expertise include consumer behavior, mar-keting research, pricing, and the evaluation of promo-tions. He has published more than 25 articles in Journalof Marketing Research, Journal of Marketing, and Jour-nal of Consumer Research. He has received university-wide teaching awards, including the Amoco TeachingAward, the Mungo Award for Teaching Excellence, and

the Trustee Professorship Award, and has twice receivedthe Moore School of Business Teacher of the YearAward. He serves as the University SEC Faculty AthleticRepresentative. He is on the editorial review boards ofJournal of Consumer Research, Journal of MarketingResearch, Journal of Marketing, and Journal of Con-sumer Psychology and was Associate Editor for Journalof Consumer Research from 1999 to 2002. He was hon-ored with the first-ever Distinguished Service Awardfrom Journal of Consumer Research in 2006. Finally,he coauthored Marketing Principles and Perspectivesand the Handbook of Marketing Scales.

ACKNOWLEDGMENTS

The authors appreciate the support of the Center forInternational Business Education and Research at theUniversity of South Carolina and are grateful to SeydaDeligonul and Varun Grover for their comments andguidance.

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