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The Ties That Bind: How CooperativeNorms and Readiness to Change Shapethe Role of Established Relationships inBusiness-to-Business E-CommerceAndrea Ordanini aa Department of Marketing, Bocconi University, Milan, Italy

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To cite this article: Andrea Ordanini (2011): The Ties That Bind: How Cooperative Norms andReadiness to Change Shape the Role of Established Relationships in Business-to-Business E-Commerce,Journal of Business-to-Business Marketing, 18:3, 276-304

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Journal of Business-to-Business Marketing, 18:276–304, 2011Copyright © Taylor & Francis Group, LLCISSN: 1051-712X print/1547-0628 onlineDOI: 10.1080/1051712X.2011.541379

The Ties That Bind: How Cooperative Normsand Readiness to Change Shape the Role of

Established Relationships inBusiness-to-Business E-Commerce

ANDREA ORDANINIDepartment of Marketing, Bocconi University, Milan, Italy

Purpose: Mainstream research indicates that close, long-term tieswith business customers have beneficial effects; however, an alter-native stream advances the possibility of a “dark side” of closerelations, especially when the original conditions of the relation-ships change. This empirical study investigates how establishedbuyer–seller relationships respond to significant changes in theirexchange context by considering the value of close ties in thepresence of an e-commerce strategy, which generally represents aradical shift.

Methodology/approach: The article explores both the directeffects of close, long-term ties on e-commerce success and the mod-erating effects of two key contingency factors (partners’ readinessand cooperative norms). Independent variables are primary datacollected from an extensive survey of 168 e-commerce adopters.Dependent variables are secondary data performance measures.The empirical model is tested using seemingly unrelated regressionand non-monotone moderation analysis.

Findings: The study reveals that the mere presence of strong,long-term customer relationships cannot guarantee performanceimprovements or enhance e-commerce potential. Instead, the twocontingency factors modify the role of established relationships,making them as either points of strength or weakness in presenceof a change. Strong non-monotone moderation effects are at work.

Research implications: The authors offer an explanation forthe contrasting evidence regarding the value of long-term ties,

Address correspondence to Andrea Ordanini, Department of Marketing, BocconiUniversity, Via Rontgen, 1, 20136 Milan, Italy. E-mail: andrea.ordanini@unibocconi.it

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exploring and understanding how to cope with the benefits ofstability and the requirements of dynamicity in vertical relations.The findings also contribute to literature on the relational driversof exchange performance, by citing elements, such as readinessto change and cooperative norms, that can make an existingrelationship either an asset or a liability.

KEYWORDS long-term ties, e-commerce, cooperative norms,readiness to change, industrial marketing, business marketing

Beginning in the late 1980s, business marketing studies started movingfrom a transaction focus, based on the mechanisms that underlie singleexchanges, to a relationship focus, considering the features of long-term tiesand the governance effects of nonmarket modes (Anderson and Narus 2004;Duncan and Moriarty 1998). This literature made a strong case for the impor-tance of establishing and developing close, long-term relationships with keycustomers (Wathne, Biong, and Heide 2001). It also has generated importantinsights into the properties of such relationships and their relational drivers(Palmatier et al. 2006). However, such studies assume implicitly that throughtheir continuity, relationships convey important benefits to clients and sup-pliers, such as reduced transaction costs, enhanced productivity, increasedswitching barriers, and higher economic returns (Crosby, Evans, and Cowles1990; Hakansson and Snehota 1995).

There is an alternative view however. Some research remains cautiousabout the positive role of long-term ties, asserting that relationships proceedthrough different phases that are characterized by distinct behaviors, pro-cesses, and orientations, so they must experience significant transitions whenthe exchange context changes (Jap and Ganesan 2000; Narayandas andRangan 2004; Wathne and Heide 2004). Because of the resulting dynamicinterplay of trust and commitment, power and dependence, and the levelof lock-in (Buvik and John 2000; Jap and Ganesan 2000), close ties eventu-ally may even destabilize the relationship in altered exchange circumstances(Grayson and Ambler 1999; Wuyts and Geyskens 2005). Therefore, the valueof relational drivers may be contingent on the environmental conditionssurrounding the relationship (Palmatier et al. 2006).

Yet little empirical research offers meaningful evidence about howestablished buyer–seller relationships respond to significant changes inthe exchange context (Lambe, Wittmann, and Spekman 2001; Narayandasand Rangan 2004; Wathne et al. 2001; Wilson 1995). To address thisissue, we explore how an event that significantly modifies the exchangecontext—whether by affecting the partners’ strategies or by changing thenorms that govern the relation—shapes the value of long-term buyer–sellerrelationships.1 In the presence of such an event, we argue that the effect ofclose ties actually is contingent on the features of the environmental context(Palmatier et al. 2006).

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Drawing on both marketing (Claycomb, Iyer, and Germain 2005; Japand Mohr 2002; Srinivasan, Lilien, and Rangaswamy 2002) and informationsystems (Barua et al. 2004; Lyytinen and Rose 2003) literature, we consideran e-commerce implementation, an event that modifies the exchange contextsignificantly and therefore may affect the value of long-term relations. Witha sample of e-commerce adopters, we empirically investigate the role oflong-term ties and two contingencies—readiness to change and cooperativenorms—that likely shape the value of long-term ties in a modified exchangesituation. The mere presence of long-term ties does not guarantee enhancede-commerce potential, and variations in the levels of readiness to change orcooperative norms can transform long-term ties from assets into liabilities.

With these findings, our analysis makes three main contributions to the-ory and practice. First, prior literature has investigated relations in a steadystate or explored internal evolutions across stages; this study examines howclose ties respond to actual changes in the exchange context (Narayandasand Rangan 2004). By tracking the value of buyer–seller links before andafter a substantial change in the market, we demonstrate that long-termties can induce either success or failure in an altered exchange context.Therefore, established relations do not per se provide firms with sufficientdynamic capabilities to face environmental uncertainty.

Second, we provide a contingent framework to assess the value oflong-term ties, in which we identify elements that make this value fully con-tingent. In particular, readiness to change helps parties adapt their strategiesand processes to the new context, and cooperative norms support mutuallybeneficial adaptations to new relational rules. These powerful contingenciestherefore have notable effects on the value of long-term ties in changed con-ditions. These findings may explain prior controversial evidence regardingthe role of established buyer–seller relations (e.g., Anderson and Jap 2005).

Third, we clarify the drivers of e-commerce success, a topic with wide-reaching implications for marketing practice (Srinivasan et al. 2002). Ourfindings pertaining to this research question shed light on prior equivo-cal results regarding the role of established relationships as facilitators ofe-commerce (Kohli and Devaraj 2003).

THEORETICAL BACKGROUND

Buyer–Seller Relations: The Bright Side

According to mainstream relationship marketing literature, the capability tobuild and manage long-term, close relationships is a cornerstone of success,especially in business-to-business (B2B) markets (Ganesan 1994; Morganand Hunt 1994). By developing strong ties with key partners through highfrequency relations that persist over time (Granovetter 1973; Marsden andCampbell 1984), firms enjoy an advantage, because winning new customersis more expensive than maintaining existing partners (Reicheld and Sasser

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1990). In addition, increasing the profitability of existing business rela-tions and extending their duration improves chances of success (Bauer,Grether, and Leach 2002). Thus, strong, well-established business relation-ships enhance seller performance outcomes, including sales growth, marketshare, and profits (Crosby et al. 1990; Morgan and Hunt 1994).

A recent meta-analysis of relationship marketing literature (Palmatieret al. 2006) has identified several theoretical perspectives supporting thepositive value of close vertical ties: commitment–trust, relational norms,dependence, and transaction costs. The first two views often appear togetherand represent the foundation of the relationship marketing view (seeDwyer, Schurr, and Oh 1987), which holds that exchange parties evaluateB2B relationships behaviorally, avoid short-term asymmetries, and focus onlong-term mutual benefits (Luo 2002). Therefore, stable ties result from trust-worthy relationships and stimulate cooperation, goodwill, and commitment(Kumar 1996), which in turn enhance both partners’ performance (Luschand Brown 1996).

The dependence perspective indicates that power is more importantthan trust as a means to promote efficiency and effectiveness in interorgani-zational exchanges (Heide and John 1988). When partners invest time andeffort to build relational governance structures, they become more depen-dent on their partners, and duplicating such bonds with another partnerwould involve additional investments. Therefore, the parties increase thefrequency and depth of their exchange, and the shared information providesvalue to each party, because it is difficult to replace (Mohr and Nevin 1990).

Finally, transaction cost theory asserts that strong vertical ties providean effective form of governance that reduces the hazards of opportunismand other forms of exploitation among exchange partners (Heide 1994). Inparticular, close relationships help safeguard asset-specific investments socompanies can adapt to uncertainty (Rindfleisch and Heide 1997).

Thus, the mainstream view implies a bright side of close, long-term ties.Drawing from different theoretical perspectives, this view sustains the notionthat establishing close buyer–seller relations is a key goal in a successfulbusiness marketing strategy. As summarized in a recent meta-analysis, “mostresearch and practice assumes that relationship marketing efforts generatestronger customer relationships that enhance seller performance outcomes”(Palmatier, Dant, and Grewal 2007: 172).

Buyer–Seller Relations: The Potential Dark Side

Parallel research instead suggests that in some circumstances, long-term tiesrepresent a liability instead of an asset (Noordewier, John, and Nevin 1990).For example, Grayson and Ambler (1999: 139) observed that in uncertaincontexts, “the sustainable competitive advantage enjoyed by long-term rela-tionships carries the seeds of its own destruction.” Some authors warn about

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negative consequences of investing too much in trust and argue that therelationship between partner selection and opportunism is unlikely to beas simple as linear models imply (Jeffries and Reed 2000; Berman et al.1999). Moreover, the benefits of close ties may be asymmetric (Kalwani andNarayandas 1995), and developing and maintaining relationships over timecan be quite costly (Wuyts and Geyskens 2005).

Most proponents of this dark side view rely on the concept of therelationship lifecycle, according to which long-term ties evolve through dif-ferent phases that induce major transitions in the partners’ view of eachother (Jap and Ganesan 2000; Narayandas and Rangan 2004; Wathne andHeide 2004). When the original exchange conditions change, the foundationof the relationship—whether trust, commitment, dependence, or lock-in—may begin to crumble, because the changed conditions demand accordantchanges by the parties and to the relationship. However, “safeguardinginvestments requires that the parties tie their hands, whereas adaptationrequires that options exist to revise anticipated courses of action” (Buvikand John 2000: 53).

Therefore, recent literature calls for studies of established buyer–sellerlinks that focus on the change events, which necessarily prompt adaptationsin the relationship strategy or adjustments to the relational behavior of thecounterparts (Wathne and Heide 2004). When events modify the context ofthe relationship, the positive role of close ties cannot be taken for granted;rather, their value becomes contingent on the new environmental conditions(Palmatier et al. 2006).

First, buyer–seller relationships represent outcomes of specific deci-sions and particular market conditions (Leek, Turnbull, and Naudè 2003).Therefore, if one partner implements an innovative strategy, it will influencethe business policies currently adopted by its counterpart. Yet the coun-terpart might not be capable of modifying its current strategy, especiallyin the presence of strong ties (Wuyts and Geyskens 2005). That is, self-enforcement literature indicates that long-term relations reduce the capacityand motivation to innovate (Baiman and Rajan 2002) or find optimal adapta-tions (Jeffries and Reed 2000). At the same time, such relations increase thetendency of firms to focus on a particular field of knowledge, ignoring exter-nal opportunities (Poppo and Zenger 1998). Therefore, unless both partnersexhibit a strong readiness to change, adjustments to the strategic mindsetmight be delayed or not achieved at all. This limitation should stress exist-ing ties and make even well-established relationships inefficient for both thebuyer and the seller (Narayandas and Rangan 2004).

Second, a firm involved in a close relation may decide to behave oppor-tunistically if it perceives that the distribution of gains that result from a majorchange has become indeterminate or unfavorable (Wathne and Heide 2004).Such opportunism may be passive, such as in the form of inflexibility ora refusal to adapt, as well as active, such as demands for renegotiation.

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Beyond its redistributive effects and delays for negotiation, opportunismoften reduces overall value creation in an exchange, because the transactionsbecome maladapted to the environment and harm both parties (Wathne andHeide 2000). However, if the relation has relied on cooperative norms tofoster a joint collaborative approach and promote reciprocity and solidar-ity, opportunistic behaviors might be limited (Cannon and Perreault 1999).Self-enforcement literature confirms that opportunism gets inhibited whenthe anticipated long-term gains of the relationship outweigh the short-termgains of cheating (Nagin et al. 2002). In contrast, if the close tie is due topower issues or lock-in phenomena, opportunism is likely and may havenegative relationship effects (Wathne and Heide 2000).

Research Framework: A Contingent View of Buyer–Seller Relations

We draw on these contrasting theoretical arguments to build a conceptualframework in which we posit that the value of long-term close ties, in thepresence of a specific change event, is contingent on two conditions: howmuch readiness to change the parties exhibit and how much their rela-tionship relies on cooperative norms. To test this framework, we considerscenarios in which a seller firm implements e-commerce. In this specificempirical setting, the model predicts that close, long-term relations will notper se lead to a tangible change in the seller firm’s performance after imple-mentation. Rather, its performance should improve or suffer, depending onthe level of readiness to change and cooperative norms in the relationship(see Figure 1).

FIGURE 1 Research framework (color figure available online).

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RESEARCH SETTING AND HYPOTHESES

E-Commerce as a Change Event

E-commerce provides an interesting research context for testing our con-ceptual model, because both marketing (Claycomb et al. 2005; Jap andMohr 2002; Srinivasan et al. 2002; Wu, Mahajan, and Balasubramanian 2003)and information systems (Barua et al. 2004; Lyytinen and Rose 2003; Zwass2003) literature call its implementation a significant event that alters theexchange context and affects existing buyer–seller relations. Specifically,e-commerce refers to “the sharing of business information, maintainingbusiness relationships, and conducting business transactions by means oftelecommunication networks” (Zwass 1996: 3), which means that it “includesboth electronic data interchange (EDI) and Web- and Internet-based applica-tions” (Claycomb et al. 2005: 222). Despite their promise though, emergingtechnologies such as e-commerce “can undermine long-term business rela-tionships . . . built and established over the course of many years” (Jap andMohr 2002: 25).

For example, the implementation of e-commerce requires strategic andorganizational changes across the entire sales selling process, from pro-curement to the sales force (Saini and Johnson 2005). When partners startto function in an electronic marketplace, both buyers and sellers mustchange their competitive marketing strategies, especially with regard to howthey deploy their marketing resources (Pires and Aisbett 2003; Varadarajanand Yadav 2002). At a more general level, executing e-commerce involvesthe concurrent adoption of new business policies by both counterparts(Claycomb et al. 2005) and demands large-scale adaptations to internal pro-cesses (Zhu et al. 2006). After an e-commerce implementation, readiness tochange should influence the extent to which parties can adapt their strategiesand processes to the new exchange context.

The implementation of e-commerce also produces effects beyond theboundaries of the focal firm (Swanson 1994) that have an uncertain pay-off and may produce asymmetric effects for the partners (Pires and Aisbett2003). Because it might alter the benefits that buyers and sellers gain fromtheir relationship, e-commerce can change the partners’ incentives and thustheir relational behavior (Wathne and Heide 2000). After implementation,the intensity of cooperative norms therefore should influence how inclinedthe parties are to engage in a mutually beneficial adaptation or else act inmore opportunistic ways.

Readiness to Change

E-commerce is a bilateral process; independent of the resources and deci-sions of the focal firm, the impact of close ties on the execution of ane-commerce strategy also depends on the behavior of the partner and its

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readiness to move online (Melville, Kraemer, and Gurbaxani 2004). In ane-commerce domain, readiness refers to the partners’ technological and busi-ness capabilities to shift their operations online (Chewlos, Benbasat, andDexter 2001). A partner’s greater readiness thus might enhance the valueof strong ties in the presence of an e-commerce implementation in twoways.

First, by facilitating information flows and reducing information asym-metry and uncertainty, greater readiness enhances the coordination benefitsusually generated by close relationships. Therefore, the commercial partnermight better appreciate the potential of e-commerce and perceive the imple-mentation as mutually beneficial. Accordingly, it should increase its effortsto assist in the implementation of the strategy (Barua et al. 2004).

Second, when both parties provide relationship-specific investments tosupport the implementation, their strong ties can better foster the strategicalignment between the parties. That is, readiness to change ensures consis-tent behavior by the counterpart and the focal firm, which implies efficiencygains through reduced learning costs and time (Claycomb et al. 2005). Strongties coupled with readiness to change should encourage an initiative, suchas e-commerce, to follow a more compatible, faster implementation path, incontrast with a situation in which the partner pursues strategies that do notmatch the new context (Parasuraman 2000).

Thus, a lack of readiness to change may negate the benefits of long-termrelationships. If the partner lacks the capabilities to adapt its organization tothe new exchange context (Hibbard, Kumar, and Stern 2001), the focal firmmight either train the unskilled partner, and thus incur the associated costsand delays, or substitute for it, in which case it must bear the risk and costsof negotiating with new partners (Wuyts and Geyskens 2005). In the lattercase, the focal firm also must consider the opportunity costs of a weaker(or even broken) tie with a long-term partner. Moreover, according to self-enforcing literature, a firm with strong, long-term ties often ignores newfields of knowledge (Poppo and Zenger 1998). If the partners lack a naturalpredisposition to change, their close ties can even become institutionalizedassets, that is, resources preserved and developed not for rational reasonsbut rather because of historical and institutional habits (Oliver 1991). In thiscase, a conservative partner likely undermines the potential of innovationsand resists the expensive investments needed to adapt its business processand strategies. These arguments indicate that a partner’s readiness to changemagnifies the value of strong ties when the focal firm decides to implementan e-commerce strategy, but a lack of such readiness mitigates the potentialof those strong ties. Therefore, we posit:

H1: Close, long-term ties affect e-commerce performance (a) positivelywhen a partner’s readiness to change is high and (b) negatively when apartner’s readiness to change is low.

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Cooperative Norms

The implementation of an e-commerce strategy modifies the future pay-offs of commercial partners, but it does not guarantee a symmetric change.One party might consider e-commerce less beneficial than its counterpart,such that the equilibrium of their relationship changes due to the imple-mentation (Kaplan and Garicano 2001). Therefore, even if both partnersare ready to and capable of change, diverging incentives may hinder theimplementation of e-commerce, because the party that anticipates earningfewer benefits likely is not willing to engage in e-commerce and may insteadexhibit opportunism (Williams and Frolich 2001).

The outcome depends on the extent to which existing ties reflectcooperative norms that mandate firms work together to achieve their goalsthrough coordination (Cannon and Perreault 1999). Cooperative norms oftenlead to strong ties, though close relationships also can result from initialpower asymmetries, through dependence and lock-in effects. Conversely, abalanced and potentially collaborative situation does not guarantee a virtu-ous cycle of commitment and trust (Narayandas and Rangan 2004; Palmatieret al. 2007).

Heide and John (1990) and Lusch and Brown (1996) both showedthat strong cooperative norms foster coordinated interaction patterns, whichencourage better adaptation. Activities might be revised or shifted with-out any formal reassignment of roles, and tightly coupled activities canbe facilitated by the reduced likelihood of controversy between coopera-tive parties (Buvik and John 2000). More cooperative norms thus induce agreater willingness to exchange information and share knowledge (Cannonand Perreault 1999), so the benefits of such established relationships shouldbe greater with regard to e-commerce performance (Wilson and Abel 2002).Because cooperative norms derive from trust, they push both partners toshare responsibilities and stimulate relationship-specific investments, whichincrease process efficiency and value (Saeed, Malhotra, and Grover 2005).

However, if a buyer–seller relationship has weak cooperative norms,the partners’ relations tend to be adversarial, and power prevails overtrust as a governing mechanism (Jap and Ganesan 2000). Therefore, ratherthan aligned behaviors, the partners may engage in opportunistic behav-iors, especially if the environment is challenging (Sharma 2002; Wathneand Heide 2000). Such partners likely perceive e-commerce initiatives asexpensive or exploitative. An e-commerce implementation also normallyrequires compatible technology strategies with channel partners to attainsupply chain capabilities (Wu et al. 2006), so a lack of cooperation shouldretard e-commerce implementation or decrease potential market share (Sainiand Johnson 2005).

Moreover, if partners show a limited willingness to engage inactions that benefit the other party, strong ties cannot protect them from

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opportunistic behavior. A change proposed by one partner does not dis-pose the other side to reciprocate, and the counterpart can refuse to adaptor try to extract concessions (Wathne and Heide 2000). Even in the pres-ence of such noncooperative behavior though, the focal firm might notbe able to change partners because of its close ties, which entail long-standing business relationships that rely on well-established routines andaccumulated expertise (Narayandas and Rangan 2004). Information systemsliterature also shows that coercive pressures provide little incentive to imple-ment e-commerce along the vertical channel (Claycomb et al. 2005), whereascompliance efforts are costly and often cause delays (Pires and Aisbett 2003).In the absence of cooperative and trusting relationships, technology systemsappear to do little but magnify existing suspicions or fracture already tenuousrelationships (Jap and Anderson 2003).

In summary, when existing ties are governed by cooperative norms,their capacity to facilitate an e-commerce implementation increases; whenthey reflect weak cooperative norms, the focal firm implements its strategy inpresence of uncooperative partners, such that the potential asset of long-runties becomes a liability. We accordingly hypothesize:

H2: Close, long-term ties affect e-commerce performance (a) positivelywhen the relationship relies strongly on cooperative norms and (b)negatively when the relationship relies weakly on cooperative norms.

MEASURES

Independent Variables and Moderators

To develop valid measures for our independent variables, we employeda discovery-oriented approach (Menon et al. 1999). To operationalize ourrelationship constructs, we carefully built measures that reflect the key ele-ments of our specific empirical context (i.e., e-commerce; Punch 2005). First,we reviewed marketing and information systems literature thoroughly togather scales for the measurement constructs. Second, we assessed thesescales with an iterative process involving theoretical suggestions from in-depth interviews with a convenience sample of 15 marketing directors, whorecommended ways to ensure the items reflected B2B e-commerce. Third,we pilot tested the full measurement instrument to confirm that the wordingwas clear and the length was appropriate.

To measure the extent of close, long-term ties, we focused on theirmost important consequences for B2B e-commerce activity: information col-lection, communication, and sharing and customization (Jap and Mohr 2002;Zwass 2003). With a four-item scale adapted from Zhuang and Lederer(2006), we measured the intensity of customer relationships from the per-spective of the focal firm that implemented the e-commerce initiative. The

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measure indicated the extent to which the firm regularly communicates withkey business customers to build long-term ties, tailors its product or servicesto suit their needs, collects information from clients, and counts on an openand frequent relationship with its counterpart.2

We operationalized partners’ readiness to change with a four-item scalefrom Barua and colleagues (2004) that reflects the firm’s perception of itsbusiness customers’ beliefs about e-commerce in terms of security and pri-vacy issues, the relevance of online exchanges, the availability of adequateWeb-based systems, and improvements to coordination and informationsharing. This construct therefore reflects the selling firm’s perception of howmuch the commercial counterpart would adapt its structure and activity toexecute an e-commerce strategy (Chewlos et al. 2001).

The measure of cooperative norms used a four-item scale fromClaycomb et al. (2005), who also applied it in an e-commerce context.Rooted in work by Cannon and Perreault (1999), this scale assesses theextent to which the firm’s partnership with key customers focuses on coop-erative rather than adversarial goals (Manohar and Narayandas 1995). Themeasure determines whether parties are concerned about each other’s prof-itability, are open to working together to be successful, never take advantageof their bargaining power, and face changes in a joint fashion (Anderson andNarus 1990).

Dependent Variables

We used two measures of e-commerce performance. The first, firm perfor-mance, refers to the firm level and represents the difference between thefirm’s financial performance before and after its e-commerce adoption. Thechoice to use observed financial indicators derives from two motivations. Arecent meta-analysis shows that perceived measures tend to be biased andoverestimate the impact of e-business strategies (Kohli and Deveraj 2003).In addition, the best existing measure of the business value of Internet-enabled initiatives uses gains in financial performance, especially in thecontext of small or medium-sized firms (as in our case; Porter 2001; Zhu andKraemer 2002). Therefore, we gather two financial ratios that appear heavilyaffected by e-commerce activity: operating income to total assets and returnon sales. The data come from the AIDA Bureau Van Djick database, whichcontains balance sheets and financial data for Italian firms with more thanten employees. We collected these measures for the last two years availableand the two years prior to the year of e-commerce adoption (Bharadwaj2000), then took the two-year mean to reduce any potential variance. Wealso normalized the items according to average industry levels for com-parison. Finally, we calculated the differences between the ratios after andbefore the adoption of e-commerce for each firm (Santhanam and Hartono2003).

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The second performance measure, e-commerce impact, is a self-reported variable that captures how much the seller firm perceives that itscurrent level of performance has been affected by its e-commerce implemen-tation. This measure helps control for potential spurious effects related tothe use of only firm-level financial measures, in the sense that process ben-efits do not necessarily lead to enhanced firm performance (Ray, Barney,and Muhanna 2004). We employ a three-item scale from Barua and col-leagues (2004) to measure how much managers perceive that e-commercehas benefitted their firm’s sales, profits, and efficiency.

Control Variables

We carefully selected meaningful control variables to increase the robustnessof our analysis. First, to control for potential halo effects, we collected thesame performance measures for each firm in the two years prior to theyear of its e-commerce adoption and then average them to reduce sporadicextreme variations3 (Santhanam and Hartono 2003). Second, we include firmsize (number of employees) as a proxy for slack resources, as well as time(number of years since e-commerce adoption), to address these potentialeffects on e-commerce outcomes (Motiwalla, Khan, and Xu 2005). We findthat the average online share of turnover was 25.1 percent, and the averageadoption time was 6.54 years, though 32 percent and 11 percent of firms,respectively, adopted e-commerce less than 3 or more than 8 years ago.Third, we include a three-item measure of e-commerce capabilities, whichreflect human resource and organizational skills, to consider the focal firm’simplementation capability (Wade and Hulland 2004). Although we initiallyincluded dummy variables for industry, they were not significant, so weremoved them to improve model parsimony.

Measurement Validation

To assess the reliability and validity of our multi-item constructs (close,long-term ties; readiness to change; cooperative norms; e-commerce capa-bilities), we performed a confirmatory factor analysis (CFA) using AMOS 18.In Table 1, we list the scale items and CFA results.

These results reveal satisfactory model fit indexes (CMIN/df = 1.17, ns;normed fit index [NFI] = .87; confirmatory fit index [CFI] = .98; goodness-of-fit index [GFI] = .91; root mean squared error of approximation [RMSEA] =.032). Each factor loading was significant, with a standardized value greaterthan .4. The composite reliability measures were all greater than .6 (.61–.81),and the average variance extracted (AVE) measures exceeded .5 (.50–.78), insupport of good convergent validity (Bagozzi and Yi 1988). For the discrimi-nant validity assessment, we compared the AVE with the correlations of each

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2

TAB

LE1

Late

ntVar

iable

s:Item

s,Lo

adin

gs,Rel

iabili

tyan

dVal

idity

ofM

easu

res

(CFA

)

Item

Load

ings

CR

AVE

Clo

se,lo

ng-

term

ties

(adap

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from

Zhuan

gan

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er20

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(M=

2.96

;SD

=.8

9).6

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eta

ilor

our

pro

duct

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d/or

serv

ices

tosu

itcu

stom

ers’

spec

ific

nee

ds.

.67

3.W

eco

llect

max

imum

amountofcu

stom

erdat

aw

ithoutin

trudin

gin

toth

eir

priva

cy.

.56

4.W

ehav

elim

ited

and

rem

ote

inte

ract

ions

with

our

key

busi

nes

scu

stom

ers

(r).

.61

Par

tner

s’re

adin

ess

(Bar

ua

etal

.20

04)

(M=

3.18

;SD

=.9

6).7

4.6

81.

Our

cust

om

ers

do

notfe

elco

mfo

rtab

lere

gard

ing

secu

rity

and

priva

cyin

e-co

mm

erce

with

our

com

pan

y(r

)..6

82.

Our

cust

om

ers

consi

der

itim

portan

tto

enga

gein

elec

tronic

com

mer

ce.

.72

3.O

ur

cust

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ers

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tern

et-b

ased

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gage

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ur

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ers

are

will

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and

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leto

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ein

form

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nel

ectronic

ally

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us.

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Cooper

ativ

enorm

s(C

layc

om

b,Iy

er,an

dG

erm

ain

2005

)(M

=2.

88;

SD=

.94)

.61

.50

1.In

our

rela

tionsh

ipw

ithbusi

nes

scu

stom

ers,

both

sides

are

conce

rned

aboutea

choth

er’s

pro

fita

bili

ty.

.51

2.In

our

rela

tionsh

ipw

ithbusi

nes

scu

stom

ers,

nei

ther

side

will

take

adva

nta

geofa

stro

ng

bar

gain

ing

posi

tion.

.78

3.In

our

rela

tionsh

ipw

ithbusi

nes

scu

stom

ers,

both

sides

work

toge

ther

tobe

succ

essf

ul.

.48

4.In

our

rela

tionsh

ipw

ithbusi

nes

scu

stom

ers,

nei

ther

side

isw

illin

gto

mak

eco

oper

ativ

ech

ange

s(r

)..6

8E-c

om

mer

ceca

pab

ilitie

s(W

ade

and

Hulla

nd

2004

)(M

=3.

40;

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.89)

.68

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1.O

ur

tech

nic

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affposs

esse

sth

ekn

ow

-how

nee

ded

tom

anag

ee-

com

mer

ceap

plic

atio

ns.

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2.O

ur

funct

ional

man

ager

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eca

pab

leto

coord

inat

ee-

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mer

ceap

plic

atio

ns

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eir

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3.W

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ckcr

oss

-funct

ional

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sto

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nIT

pla

nnin

gan

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nes

sst

rate

gy(r

)..7

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t(a

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from

Bar

ua

etal

.20

04)

(M=

3.08

;SD

=.8

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1.7

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cehas

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ifica

ntly

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ease

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esa

les

ofour

firm

inth

ela

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ars.

.72

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om

mer

cehas

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gnifi

cantly

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ease

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epro

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(r).

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ifica

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Fitin

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2=

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FI=

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”

288

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Established Relationships in B2B in E-Commerce 289

TABLE 2 Discriminant Validity: Correlations (Off-Diagonal) and Average VarianceExtracted (Diagonal)

Variable A B C D E

A. Close, long-term ties .61B. Partners’ readiness to change .17 .50C. Cooperative norms .09 -.11 .68D. E-commerce capabilities -.02 .20 -.44 .60E. E-commerce impact .16 .26 .25 .17 .78

construct (Fornell and Larcker 1981) (see Table 2). In support of discrimi-nant validity, the lowest AVE level is .50, whereas the highest correlationbetween latent constructs is .44.

METHODOLOGY

Sampling and Data Collection

We extracted a stratified random sample of 1,500 firms with more than 10employees from the most recent Italian Census Information Database. Thestratification ensured that the sample reflects the structural features of thepopulation, in terms of both the number of employees (five categories)4

and industry representation (four-digit level). The questionnaire survey usedcomputer-aided telephony inquiry, conducted during the first half of 2009,and 602 firms agreed to participate in the survey.

Of the 602 interviewed firms, 188 (31 percent) recently had adoptede-commerce at the B2B level and therefore shifted some of their exchangesto online platforms. An adopter is any firm that has implemented at least oneof the following options to sell goods online: (1) extranets and virtual pri-vate networks, (2) EDI networks, or (3) third-party e-marketplace (Claycombet al. 2005). We obtained the date of the first online transaction realizedwith a main business customer, which provides the watershed for the pre–vs. post–e-commerce adoption periods. The rate of e-commerce adoptionis consistent with current rates among European firms (Ebusinesswatch2006). To limit our sample to brick-and-mortar firms that have imple-mented e-commerce substantially, we only included those organizationsthat declared they derived at least 10 percent of their annual turnoverfrom online transactions (Amit and Zott 2001). We excluded 20 firmsfor which we lacked post-adoption performance measures, because theire-commerce adoption date was less than a year prior to our data col-lection. The final sample thus consists of 168 firms. Compared with therelevant population, our e-commerce adopters were slightly larger (70 vs. 44employees), though the distribution across industries showed no significantdifferences.

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290 A. Ordanini

For the self-reported survey, we trained interviewers about the contentof the survey and conducted several meetings to discuss potential concernsbefore and after the pilot test (Frey 1988). We selected firm CEOs as keyinformants, because our sample mainly consists of small to medium-sizedfirms, and prior evidence in both marketing (Claycomb et al. 2005) andinformation systems (Barua et al. 2004) research shows that smaller organi-zations consider e-commerce a firm-level innovation. The CEOs can respondon behalf of the entire organization. Our field interviews support this choice;in each case, the CEO was responsible for the e-commerce implementationin his or her firm. Furthermore, we asked the informants to provide self-assessments of their knowledge on the topic (Wu et al. 2003) and obtain amean response of 4.34 on a five-point scale.

The interview instructions asked the informants to focus on rela-tionships with their most important customers, which is consistent withrelationship marketing literature that indicates close, long-term ties are usu-ally with a few important commercial partners (Manohar and Narayandas1995; Wathne et al. 2001). Moreover, it is consistent with previous B2Be-commerce research, which shows that online exchanges develop first witha few relevant clients (Claycomb et al. 2005). Finally, this choice increasesthe validity of our findings, because it enables respondents to concentrateon a specific and narrow domain (Kumar, Stern, and Anderson 1993).

To increase response rates, we limited the length of the questionnaire sothat the CEOs could complete it in eight to ten minutes on average; they alsocould reschedule the appointment. We promised incentives to participants:an executive summary of the research and an invitation to participate in auniversity workshop to discuss the outcomes.

Because our focal constructs—close, long-term ties, readiness tochange, and cooperative norms—come from respondents on the seller side,their measures inevitably reflect the perception of one side. To ensure thevalidity of these measures, we asked each key informant to provide thename of at least one contact from their most important client organization,for our collection of validation data (Wuyts and Geyskens 2005). We thencontacted the contact persons in the client organizations and asked them toassess the three focal constructs in relation to the specific seller. We obtainedinformation from 61 client firms, so for these dyads, we can compare sell-ers’ and buyers’ assessments. The inter-rater reliability indexes indicate agood level of agreement, with values of .77 for cooperative norms, .73 forlong-term ties, and .82 for readiness to change. Although the buyers’ scoreswere consistently higher, we detected no significant differences, in supportof measure validity.

For the secondary data (i.e., performance measures), we used the AIDABureau Van Djick database, which contains balance sheets and financial datafor Italian firms with more than ten employees. We avoid financial marketindicators because few Italian firms are listed on a stock exchange. As noted

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Established Relationships in B2B in E-Commerce 291

previously, we collected these data at both firm and industry levels and atboth the time of e-commerce adoption and the present.

Analytical Model

We used a hierarchical moderated regression approach to investigate ourdata (Aiken and West 1991) and analyze the main and moderated effects ofclose ties on firm performance among e-commerce adopters. The two mul-tiple regression equations use firm performance and e-commerce impact asthe dependent variables. The high correlation of these two measures of per-formance (r = .68) indicates that a separate estimation with ordinary leastsquare regression models would be inadequate and lead to biased, inconsis-tent results, because the errors would correlate across equations (Johnstonand DiNardo 1997). A Breusch-Pagan test (χ 2 = 77.41, p = .00) confirmsthe significant contemporaneous correlation among the error terms acrossthe equations, and the endogenous variables are not stochastically indepen-dent of the error terms. Therefore, we test the hypotheses using seeminglyunrelated regression (SUR), which is appropriate for analyzing a system ofmultiple equations with cross-equation parameter restrictions and correlatederror terms (Zellner 1962).

We estimate two pairs of SUR models: The first pair contains all controlsand the main effects of all independent variables on performance mea-sures, and the second pair includes the interaction terms between close,long-term ties and our two key moderators, readiness and cooperativenorms. We mean-center each variable before creating the interaction termsto avoid collinearity and facilitate the simple effects interpretation (Irwin andMcClelland 2001).

Because our framework implies that the effects of close ties on firmperformance after the implementation of an e-commerce strategy are non-monotonic (i.e., shifting from positive to negative), depending on the degreeof readiness to change or cooperative norms, we need a specific procedureto test our moderation hypotheses (Wathne and Heide 2004). Simply inspect-ing the sign and magnitude of the interaction terms in regression equationscannot reveal the presence of nonmonotonic effects, because symmetricalmoderation impacts can be assumed (Schoonhoven 1981). Therefore, wecalculate the partial derivative of each regression equation to determine howmuch performance changes in presence of a one-unit increase in the levelof close ties. We next inspect the inflection point of the partial derivative,which is the value of the moderator when the derivative equals 0. At thispoint, the partial derivative changes its sign; that is, at the identified val-ues of readiness to change and cooperative norms, the performance changedue to a one-unit change in the level of close ties shifts from positive tonegative. Finally, we determine if this inflection point falls inside or out-side the range of values of the moderator variables. If inside this range, the

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292 A. Ordanini

nonmonotonic moderation hypotheses receive support, because the influ-ence of close ties on e-commerce performance is either positive or negative,depending on the values of readiness to change and cooperative norms. Ifinstead the point is outside the range, a moderation effect may exist but willbe monotonic, and the impact of close ties on e-commerce performancevaries but remains persistently positive or negative, regardless of the levelof readiness to change and cooperative norms (see the appendix for furtherdetails).

RESULTSPreliminary Findings

In Table 3, we provide the outcomes of the SUR analyses. For the maineffects (Model 1), we note that the mere presence of close, long-termties has a negligible effect on firms’ performance after their e-commerceimplementation. The coefficients related to this main effect never differ sig-nificantly from 0 for firm performance (b = .10, ns) or e-commerce impact(b = .15, ns). That is, in support of our preliminary assumption, the ben-efits generated by close, long-term ties are not guaranteed in the presenceof changed exchange conditions. Furthermore, our findings confirm key

TABLE 3 Results of Seemingly Unrelated Regression Analyses

Firm performance(after adoption)

E-commerce impact(after adoption)

Variable Model 1 Model 2 Model 1 Model 2

Constant controls 2.43 2.35 −2.02 −2.21Firm performance

before e-commerceadoption

0.04 (0.02) ∗ 0.05 (0.02) ∗ 0.13 (0.04) ∗ 0.13 (0.04) ∗

Years of e-commerceadoption

0.04 (0.04) 0.05 (0.04) 0.20 (0.08) ∗ 0.22 (0.08) ∗

Size −0.00 (0.00) −0.00 (0.00) −0.01 (0.00) ∗ −0.01 (0.00) ∗

E-commercecapabilities

0.18 (0.08) ∗ 0.20 (0.07) ∗ 0.74 (0.15) ∗∗ 0.77 (0.15) ∗∗

Main effectsCooperative norms 0.32 (0.08) ∗∗ 0.33 (0.08) ∗∗ 0.86 (0.16) ∗∗ 0.90 (0.16) ∗∗

Readiness to change 0.19 (0.07) ∗ 0.22 (0.07) ∗∗ 0.41 (0.14) ∗ 0.48 (0.14) ∗∗

Close, long-term ties 0.10 (0.07) 0.12 (0.07) 0.15 (0.14) 0.19 (0.14)Interactions

H1: Long-term ties ×Cooperative norms

0.19 (0.09) ∗ 0.42 (0.17) ∗

H2: Long-term ties ×Readiness to change

0.15 (0.07) ∗ 0.30 (0.14) ∗

R2 0.20 0.24 0.36 0.39χ 2 42.54 52.14 93.23 106.52

∗p < .05. ∗∗p < .01.

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Established Relationships in B2B in E-Commerce 293

indications from information systems literature; the level of clients’ readinessto change and extent of cooperative norms act as powerful predictors of thesuccess of an e-commerce strategy.

With regard to the interaction terms (Model 2), we first observe thatboth readiness to change and cooperative norms significantly affect the rela-tionship between close ties and performance after the e-commerce adoption.That is, they can shape the role of long-term ties when conditions change.The interaction terms between close ties and readiness to change (H1) arepositive and statistically significant for both performance measures (firmperformance b = .22, z = 2.13; e-commerce impact b = .48, z = 2.17).The effect of close ties is greater when partners are more ready and lesserwhen they are not ready to change; thus, long-term ties provide a point ofstrength in altered situations, because business counterparts can address andstrategically align themselves with the changes.

The interaction terms between close ties and the extent of cooperativenorms (H2) also are positive and statistically significant for both performancemeasures (firm performance b = .19, z = 2.19; e-commerce impact b = .42,z = 2.38). Thus, the effect of close ties on e-commerce success increaseswith a greater inclination to manage business relations cooperatively butdecreases when those relationships are based on adversarial behaviors.The extent of cooperative norms appears to allow the firm to leveragethe potential of its close ties effectively, because they facilitate adjustmentsto the rules and relationship mechanisms in the presence of a contextualchange.

Moderation Effects

In Figure 2, we summarize the nonmonotonic moderation analysis wedescribed previously (see the appendix). When the contingent factors reachtheir average values (i.e., 0 along the horizontal axes), the impact oflong-term ties on performance after the e-commerce implementation isnegligible. This impact becomes positive when cooperative norms and readi-ness to change increase beyond certain levels, but it is negative when thecooperative norm and readiness to change levels decrease.

According to the procedure we describe in the appendix, the maineffect of close ties on firm performance after e-commerce implementation is0 when readiness to change and cooperative norms reach the mean-centeredvalues of −.79 (−.12/.15) and −.62 (−.19/.30), respectively. Similarly, themain effect of long-term ties on e-commerce impact after implementation is0 when readiness to change and cooperative norms indicate mean-centeredvalues of −.61 (−.12/.19) and −.45 (−.19/.42), respectively. Because allthese inflection points fall within the range of possible values for both readi-ness to change (min –2.18, max +1.82, mean-centered) and cooperativenorms (min –1.88, max +2.12, mean-centered), we find support for our

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–.61

–.5

0.5

1

d(E

com

_im

pact

)/d(

Long

term

ties

)

–2 –1 0 1 2

Readiness to change (centered)

–.79

–.2

0.2

.4

d(F

irm_p

erf)

/d(L

ong

term

ties

)

–2 –1 0 1 2

Readiness to change (centered)

–.45

–.5

0.5

1

d(E

com

_im

pact

)/d(

Long

term

ties

)

–2 –1 0 1 2

Cooperative Norms (centered)

–.62–.

20

.2.4

.6

d(F

irm_p

erf)

/d(L

ong

term

ties

)

–2 –1 0 1 2

Cooperative Norms (centered)

FIGURE 2 Nonmonotonic moderation effects (color figure available online).

nonmonotonic moderation hypotheses. The influence of close ties on per-formance after e-commerce implementation is either positive or negative,depending on the values of readiness to change and cooperative norms.

If partners’ readiness is less than −.79 (21 percent of the cases) or−.61 (22 percent), the impact of long-term ties on e-commerce success,as measured by firm performance and e-commerce impact, respectively, isnegative, in support of H1b. Conversely, when readiness to change exceedsthese values, the impact of long-term ties on performance becomes positive,in support of H1a. These findings reveal that B2B customers’ readiness canturn long-lasting relationships into either a benefit or a liability, dependingon the value of contingent factors.

Similarly, when the value of cooperative norms is less than −.62 (33percent) or −.45 (33 percent), the impact of long-term orientation one-commerce success, in the form of firm performance and e-commerceimpact, respectively, is negative, in support of H2b. At higher levels of coop-erative norms, the impact of long-lasting ties instead is positive, in support ofH2a. Again, the presence of cooperative norms can make close relationshipseither a point of strength or a weakness for e-commerce success.

Overall, the dark side—that is, when long-term ties are detrimen-tal to e-commerce implementation—occurs in 21 to 33 percent of thecases (depending on the performance measure). Therefore, readiness and

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cooperative norms not only moderate the relationship between long-termties and performance but also can reverse its sign, which implies that strong,nonmonotonic, contingent effects are at work.

DISCUSSION AND CONCLUSION

By considering a central theme of industrial marketing literature—the roleof long-term ties in a B2B context—this study contributes to existingknowledge with a contingent analysis of ties’ value in the course of anenvironmental change. This research therefore responds to calls for furtherinvestigations of the life-cycle of long-term relationships (Jap and Ganesan2000; Wathne and Heide 2004), as well as how relational ties evolve andrespond to internal and external changes (Narayandas and Rangan 2004;Palmatier et al. 2007).

We develop and test a framework to assess the value of long-lastingrelationships in the presence of an e-commerce strategy, a circumstancethat modifies the original conditions of the relationships and affects bothpartners’ strategies and relational behavior (Jap and Mohr 2002). By track-ing performance before and after an e-commerce implementation, whilecontrolling for several other potential effects, we reveal that relationshipcloseness per se does not exert a tangible effect on a firm’s performancechange. However, the presence of long-term ties can become an asset or aliability, depending on the role of two contingencies: the partner’s readinessto change and the presence of cooperative norms in the relationship.

Implications for Theory

Our analysis offers a potential explanation for the contrasting evidenceregarding the value of long-term ties, which might “serve defensive purposesby acting as switching barriers” (Wathne et al. 2001: 54) but also “carry theseeds of their own destruction” (Grayson and Ambler 1999: 139). In particu-lar, we show that existing ties sometimes bind firms rather than helping themdeal with strategic change. Although ties can be crucial assets in a stable sit-uation, they often become cospecialized resources (Madhavaram and Hunt2008) in the presence of a change, and their final value depends on severalother conditions. Thus far, close relations have been investigated mainly insteady-state contexts (Narayandas and Rangan 2004; Wuyts and Geyskens2005), but the varying reactions of partners to environmental changes overthe lifetime of their relationship may be the basis of contradictory find-ings about the role of long-term ties. Our findings reinforce the propositionby Anderson and Narus (2004) that close ties seem fairly stable over longperiods of time, but then appear far more dynamic when studied closely.In short, exploring and understanding how to cope with the benefits of

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stability and the requirements of dynamicity represents a key research taskfor industrial marketing literature; our analysis represents a first step in thisdirection.

In addition to recognizing the contingent rather than absolute valueof existing relationships, we identify two specific factors that shape thevalue of long-term ties in the presence of a change: readiness to changeand cooperative norms. Our findings contribute to literature on the rela-tional drivers of exchange performance (Palmatier et al. 2006; Rindfleischand Moorman 2003) by citing elements that can make an existing relation-ship either an asset or a liability. The levels of both readiness to changeand cooperative norms determine the value of long-term ties as conditionschange: When they are low, close ties bind parties to an inefficient con-text, but when they are high, close ties facilitate the exploitation of the newcontext. Specifically, readiness to change indicates a capability to adapt tonew exchange conditions, which highlights the role of resource dependency(Buvik and Gronhaug 2000; Heide 1994), in the sense that even despite afirm’s best efforts, relational success requires the capabilities of commer-cial counterparts. All else being equal, firms with more adaptive businesscustomers should deal better with changes that reshape the structure oftheir relationships. Cooperative norms instead pertain to a willingness toadapt. When long-term ties lack the support of high levels of cooperation,an external change can create room for unilateral moves by parties that aimto exploit the new conditions (Wathne and Heide 2000). Even if a counter-part is capable of addressing changing conditions, only long-term relationsbased on cooperative norms can give that counterpart an incentive to actcooperatively, such that the close tie becomes an asset and the partners canmutually exploit the new situation.

Finally, we contribute to e-commerce literature and respond to calls forresearch into the value drivers of e-commerce implementation (Claycombet al. 2005; Srinivasan et al. 2002). Our analysis provides empirical supportto the proposition by Jap and Mohr (2002: 25) that “e-commerce technolo-gies cannot be successfully leveraged without considering the organizationalrelationships in which the technologies are being embedded.” Without ade-quate adaptation capabilities (i.e., readiness to change) and relationshipsbased on solidarity (i.e., cooperative norms), e-commerce is likely to fail. Wethus provide an explanation for the equivocal results presented in previouse-commerce literature (Kohli and Devaraj 2003).

Implications for Practice

Our findings regarding the contingent value of close relationships in thepresence of contextual change offer key suggestions for practitioners. First,if the adaptation capabilities of business customers matter, marketing man-agers need to consider this element when selecting partners for long-term

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Established Relationships in B2B in E-Commerce 297

ties. Switching costs tend to be high in B2B markets, and the choice of akey partner is not an easily reversible decision (Dwyer et al. 1987). Ourresults identify adaptation capabilities as a relevant assessment criterion forpotential relational partners. That is, firms should realize that even if partnerswith a high readiness to change seem less profitable in the short term, theymay be better prepared to address changes and thus can better maintain asuccessful, long-term B2B relationship.

Second, managers should invest in efforts to develop a cooperationcontext in their relationships with key customers. Beyond the traditionaladvantages of this relational driver (Palmatier et al. 2007), the establishmentof cooperative rules enables parties to adapt to new circumstances, becauseany outcomes are perceived as joint and interdependent, not a competitionin a zero-sum game. Managers that can prevent any sense of exploitativeprofits can help support the evolving nature of the relationship, enhance therole of bilaterally beneficial strategies, and reduce the chances of opportunis-tic behaviors that can derail relationships (Jap and Ganesan 2000; Wathneand Heide 2000).

Third, the fate of an e-commerce innovation—and perhaps other strate-gies that shape existing business relations—depends on the relationalcontext. Jap and Mohr (2002) have posited that the interplay betweentechnology capabilities and the relationship contexts surrounding these tech-nologies is critical. Our analysis offers empirical proof of this interdependenteffect and tells managers that in situations marked by low readiness tochange and weak cooperative norms, a shift to e-commerce may hurt theirfirm’s performance.

Limitations and Further Research

As in any analysis, our contributions must be viewed in light of their lim-itations. First, our analysis is specific to its national context. The samplepossesses good external validity, but the structural peculiarities of the Italiansystem (e.g., high share of small businesses, specialization in traditionalindustries) must be taken into consideration before extending or general-izing our findings. Second, we concentrated on analyzing two contingencyeffects, but other potential moderators, such as learning orientation or per-sonal vs. organizational relationships (Palmatier et al. 2006), could influencethe role of established relationships in an e-commerce context. Their con-sideration in additional research would purposefully extend our findings.Third, we tested our model at the firm level, though resources may beembodied in specific processes and activities, such that performance at thefirm level might result from competitive advantages and disadvantages atthe process level (Ray et al. 2004). Although for the firms in our sample, e-commerce represented a radical innovation (Debruyne and Reibstein 2005);we cannot ignore the possibility that some spurious correlations influenced

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our dependent variable. Fourth, our analysis relies on the perceptions ofone side of the relationship (the seller) and focuses on long-term ties withkey customers instead of on single relationships. These choices are wellsupported by extant literature, but they also leave room for finer-grainedanalyses that extend our contribution.

Despite these limitations, our study offers a response to important callsfor research into how established relations shift when the context wherethey have been developed changes. We investigate the issue empiricallyby investigating the decision to shift to e-commerce and its impact onthe value of long-term ties, depending on two important contingent fac-tors. Further research should proceed along this promising research pathto expand knowledge on the mechanisms by which the development ofbusiness relationships leads to value creation.

NOTES

1. Unless otherwise indicated, throughout this text, we consider relations or ties vertical (buyer–seller) links.

2. This measure is consistent with prior literature, in that it can represent situations in which strongties result from the presence of collaborative mechanisms or because of dependence, lock-in, or powerissues (Narayandas and Rangan 2004; Palmatier et al. 2006).

3. With this control, we can detect the impact of our core constructs on firms’ relative performanceafter e-commerce implementation, because we take into account the level of relative performance thesefirms achieved before the change event.

4. The size categories were 10–19, 20–49, 50–249, 250–499, and more than 500 employees.

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APPENDIX: ANALYTICAL TECHNIQUE FOR DETECTING THEMONOTONIC EFFECT OF MODERATION

Assume a regression equation [Y = a + b1X1 + b2X2 + ε]. To test themoderation effect that X2 may have on the relationship between X1 and Y(i.e., how this relationship changes according to the different levels of X2),the new equation becomes:

[Y = a + b1X1 + b2X2 + b3X1X2 + ε

],

where X1X2 is the product term, and b3 is its effect size. Therefore, the totaleffect of X1 on Y is

[Y = b1X1 + b3X1X2],

which can be rewritten as a partial derivative:

[δY/δX1 = b1 + b3X2].

The point at which X1 has no effect on Y is a point of inflection in thepartial relationship between X1 and Y, such that

[δY/δX1 = b1 + b3X2 = 0].

This point is also where the value of X2 is the (negative) ratio between thecoefficient of the main effect of X1 (b1) and that of the c term (b3),

[X2 = −b3/b1].

If the ratio between the two coefficients falls out of the range of possiblevalues for X2, the moderation effect is monotonic, and whatever the value ofX2, the partial linear relationship between X1 and Y never changes its sign.If the ratio is a possible and meaningful value of X2, for a range of valuesof X2, the effect of X1 on Y will be positive, whereas for the remainder, itis negative. Plotting the values of the partial derivative equation provides agraphical representation of this phenomenon.

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