Steven H. Dahlquist & David A. Griffith
Multidyadic Industrial Channels: Understanding Component Supplier Profits and Original Equipment Manufacturer Behavior
Industrial component suppliers (CSs) work to enhance profitability by building brand differentiation with original equipment manufacturers (OEMs) and indirect industrial buyers (IIBs) through their marketing investments to each member. However, as a CS increases its marketing investments to its IIB, the OEM’s profit position is threatened, motivating the OEM to respond with aligning or opposing behavior. The results from a three-study, multimethod design indicate that a CS’s strategy of allocating its marketing investments between its OEM and IIB increases its brand differentiation, which allows it to capture increased profits subject to conditions of uncertainty. However, the results also demonstrate that the OEM does not sit idly by as its CS invests in building brand differentiation with the IIB; rather, it reacts with both aligning and opposing behaviors to benefit from the CS’s investments as well as offset the CS’s gains.
Keywords: multidyadic industrial channels, component supplier, original equipment manufacturer, indirect industrial buyer, opposing, aligning
M
ultidyadic industrial channels are vertical channels consisting of a component supplier (CS), which provides component parts for integration into an original equipment manufacturer’s (OEM’s) product, which the OEM then supplies to an indirect industrial buyer (IIB). For example, Siemens manufactures the electromechanical drives that Mitsubishi incorporates in its machine tools, which it then produces for Ford; and Parker Hannifin manufactures the high-pressure valves and fittings that Air Products incorporates in a chemical delivery system that it builds for Exxon-Mobil’s gas refining. Although the CS– OEM and OEM–IIB relationships are direct, it is important to note that the CS aims to establish brand differentiation with both the OEM and the IIB (to which it does not directly supply) to enhance its profits. However, the CS’s
effort to build brand differentiation with both the OEM and the IIB presents several marketing challenges. For example, consider the multidyadic industrial channel consisting of DuPont, Applied Materials, and Intel (see Figure 1). DuPont, as a CS, manufactures highly engineered and specialized plastics (e.g., fluoropolymers, elastomers) for use in semiconductor fabrication equipment. Semiconductor fabrication equipment (incorporating plastic compoFIGURE 1 Multidyadic Industrial Structure Example
DuPont
Steven H. Dahlquist is Assistant Professor of Marketing, Department of Marketing and Hospitality Services Administration, College of Business Administration, Central Michigan University (e-mail:
[email protected]). David A. Griffith is Department Chair and Professor of Marketing, Department of Marketing, College of Business and Economics, Lehigh University (e-mail:
[email protected]). The authors thank Robert Lusch, Stephen Kim, Jessica Hoppner, Roger Calantone, Cornelia Droge, Tobias Schoenherr, the reviewers of the Institute for the Study of Business Markets, and three anonymous JM reviewers for their comments and insights regarding this work. This article is based on the first author’s doctoral dissertation. Funding for this research was provided by the Institute for the Study of Business Markets of Pennsylvania State University. The content of this research reflects the views of the researchers, who are solely responsible for the accuracy of the data presented herein. Aric Rindfleisch served as area editor for this article.
© 2014, American Marketing Association ISSN: 0022-2429 (print), 1547-7185 (electronic)
Applied Materials
Intel
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Component Supplier
Original Equipment Manufacturer
Indirect Industrial Buyer
Journal of Marketing Vol. 78 (July 2014), 59–79
nents) is manufactured by OEM Applied Materials and procured by semiconductor manufacturer Intel (i.e., an IIB of DuPont). Although DuPont sells directly to Applied Materials, it also allocates marketing investments to Intel to build brand differentiation that it can leverage in its relationship with Applied Materials to enhance its profits. This creates two challenges. The first challenge is whether DuPont can leverage the brand differentiation gained through its marketing investment allocations across its OEM and IIB into profits. The second challenge is whether DuPont’s efforts to build brand differentiation with Intel go unnoticed by Applied Materials. To protect its profit position, Applied Materials must decide whether to respond and, if so, whether it should engage in behavior to align (i.e., behavior intended to leverage the effect[s] of the CS’s allocation of marketing investments) with DuPont’s brand differentiation, oppose (i.e., behavior intended to reduce the effect[s] of the CS’s allocation of marketing investments) its brand differentiation, or both. Although multidyadic industrial channels are common, little research has examined this context. Extant research has focused predominantly on dyadic relationships (e.g., Ghosh and John 2005; Heide and Weiss 1995). This is a shortcoming in the literature because researchers have demonstrated the importance of the effects that other actors introduce in the networks containing the focal dyad (e.g., Kim et al. 2011; Kumar, Heide, and Wathne 2011; Wuyts et al. 2004). For example, research in multidyadic contexts includes the analysis of agents’ downstream efforts (e.g., dependence balancing) to safeguard upstream channel investments (Heide and John 1988), the strength-of-tie effects on buyer preferences in triadic (supplier, vendor, and buyer) vertical marketing settings (Wuyts et al. 2004), and the effects of internal and external governance alignment (relative to suppliers) on manufacturer performance (relative to customers) (Kumar, Heide, and Wathne 2011). However, with the exception of Wuyts et al. (2004), empirical research has been silent on the dynamics of a multidyadic relationship comprising three interdependent dyads. Because the direct link from the CS to the IIB introduces important challenges and opportunities for all three participants— most notably in relation to effects on profits resulting from allocations in marketing investments by the CS to the IIB and resultant behaviors by the OEM—failure to consider the effects and implications of the additional dyad represents a limitation in the literature. This study aims to overcome this limitation and contributes to the literature in two ways. First, drawing on market-based asset research (e.g., Srivastava, Shervani, and Fahey 1998), we demonstrate how the CS’s marketing investment allocation influences brand differentiation in the multidyadic channel. We advance the literature (e.g., Frazier 1999; Gerstner and Hess 1995) by demonstrating that a CS’s allocation of marketing investments across the OEM (a push strategy) and the IIB (a pull strategy) builds a CS’s brand differentiation, which it can then leverage to increase its profits. Furthermore, we demonstrate that the leveraging of brand differentiation into CS profits does not occur in isolation but is influenced by 60 / Journal of Marketing, July 2014
the context of the exchange—specifically, market uncertainty and performance ambiguity. Second, we add to extant research by demonstrating the effect of a CS’s investment allocation on OEM behavior. Our findings show that the OEM does not sit idly by as the CS increases its marketing investment allocations to its IIB. Rather, OEMs respond to such investment allocations by engaging in both opposing and aligning behaviors, with the effect of brand differentiation on aligning behaviors decreasing with increased levels of OEM market uncertainty and performance ambiguity. We further demonstrate that demand (static vs. increased) and specification (whether an IIB specifies the CS’s product in its dealings with the OEM) influence not only CS profits but also OEM opposing and aligning behavior.
Multidyadic Industrial Channel Context
Investment Allocation in the Multidyadic Industrial Channel
Component suppliers must decide how to allocate marketing investments to both the direct customers that integrate their components (i.e., the OEM) and the ultimate consumer of their product (i.e., the IIB). In conceptualizing the CS’s allocation of marketing investments to an OEM and IIB, we adopted a “zero-sum” approach, as suggested by Wernerfelt’s (1994) market efficiency model; that is, given multiple opportunities to invest in customers, the overall investment the CS makes does not increase but rather is allocated across opportunities. As such, investment allocation is a percentage allocation of a fixed level of marketing investments, anchored by 100% investment in the OEM and 100% investment in the IIB. This approach is consistent with Frazier’s (1999) argumentation when considering a manufacturer’s investment allocations to its channel partners and end customers. Through this allocation, the CS can build brand differentiation, resulting in the stimulation of demand and potential CS specification by the IIB. Srivastava, Shervani, and Fahey (1998) argue that brand equity is a relational market-based asset that firms can leverage to attain profits. They note (p. 4) that “if marketbased assets are to contribute to customer and financial value,” they must be (1) convertible (i.e., they can be used to exploit an opportunity and/or neutralize a threat), (2) rare (i.e., if possessed by multiple rivals, their potential for value is diminished), (3) imperfectly imitable (i.e., they must be difficult for rivals to imitate), and (4) imperfect substitutes (i.e., rivals do not possess strategically convertible assets). We argue that a CS’s ability to differentiate its products (i.e., brand differentiation) is reflective of “superior product functionality” and, to some extent, meets these four criteria. Leveraging Brand Differentiation to Enhance Profits
Underlying marketing investments (e.g., direct selling, participation in industry trade shows, other marketing activities) and their allocation between the OEM and the IIB is the CS’s objective to build brand differentiation and, ulti-
mately, profits. According to Ghosh and John (1999), firms’ behavior toward one another is often based on their desire to increase prospective overall value such that each can increase its individual profits. How firms enhance value and subsequently share the profits of those initiatives has been the subject of dyadic empirical research (e.g., Ghosh and John 2005; Jap 1999, 2001). In the current research, we argue that a CS’s marketing investments include efforts to enhance the value of the OEM’s and IIB’s products and thereby to increase its potential to gain higher profits from the sale of its product. Assuming that the marketing investment allocation is a zero-sum approach, greater allocation to one results in lower investment in the other (note that the value the CS creates for the OEM or IIB may be channel member specific). This trade-off suggests that the CS must consider the potential for value creation with each and choose an appropriate allocation ratio. In addition, because the CS’s direct customer is the OEM, a primary objective of its marketing investments (i.e., profits) is tied to its product sales to the OEM. This approach is consistent with the interorganizational literature stream in which sellers invest in relationships with customers with the expectation that the customers will contribute to their profits (Palmatier 2008). Similar to “targeted pull” (Gerstner and Hess 1995), the CS’s objective is to build on its brand differentiation in the product marketplace such that (1) the demand for the CS’s product increases, (2) the IIB expresses a preference for the integration of the CS’s product into the OEM’s product, and (3) the OEM wants to use the CS’s product. As brand differentiation builds with the IIB—potentially to a point at which the CS’s product is “solely specified” by the IIB— the CS’s ability to leverage that differentiation in its dealings with the OEM also increases. For example, DuPont’s initiative to create “pull” for its product from Intel (the IIB) might prove effective, but in doing so, Applied Materials’ (the OEM’s) ability to select its suppliers is constrained. This strategy may enable DuPont to not only enhance but also leverage its brand differentiation with Intel to increase its profits in its relationship with Applied Materials. Although firms can leverage brand differentiation to enhance profitability, research has indicated that uncertainty influences firm strategy effectiveness (e.g., Ghosh and John 2005, 2009; Kumar, Heide, and Wathne 2011; Wathne and Heide 2004). In the multidyadic industrial channel, CSs aim to leverage brand differentiation into profits, but the effectiveness of doing so is conditional on two forms of uncertainty: market uncertainty (i.e., environmental) and performance ambiguity (i.e., behavioral).1 We define “CS market uncertainty” as the CS’s difficulty in predicting its product design as required by its customer(s). This definition, though narrower than Wathne and Heide’s (2004) definition of the extent to which it is difficult to predict changing customer needs and preferences, is consistent with the context of the multidyadic industrial channel. We focus on product design unpredictability as CS market uncertainty because 1In this article, we separately specify CS and OEM market uncertainty and performance ambiguity given the contextual differences in the types of uncertainties these members face in the multidyadic industrial channel.
industrial markets require manufacturers to alter their product designs to meet customers’ unique needs (Ghosh and John 2005). Increased market uncertainty enhances the IIB’s need for its upstream suppliers to be flexible and responsive. We define “CS performance ambiguity” as the CS’s difficulty in observing the installation, use, and performance assessment of its product by its customer(s). This definition is consistent with Ghosh and John (1999), though narrower in scope given the context examined. Increasing levels of performance ambiguity in the industrial channel expose the CS to increased costs related to misdirected efforts (Ghosh and John 2009), such as the CS having to replace components that are not actually faulty, and potential opportunism (Stump and Heide 1996), such as the OEM aiming to gain a negotiating advantage over the CS. Thus, although the CS may still leverage its brand differentiation, it will incur additional costs. OEM Behavior in Response to CS Marketing Investments to the IIB
It is important to note that although a CS’s increasing allocations of marketing investments to its IIB can create brand differentiation that it can leverage to increase profits, the OEM is not a passive actor. Although risk neutrality underlies interorganizational theory (see, e.g., Williamson 1975), the OEM recognizes that it could be harmed (from CS opportunism) or could benefit from the CS–IIB relationship (i.e., differentiating capability). Pennings and Wansink (2004) demonstrate that risk and uncertainty often influence channel decisions. In the multidyadic industrial channel, the OEM’s risk assessment motivates its behavior, and it may oppose, align, or pursue both strategies in light of the effects of the CS’s investment allocations. First, an OEM may adopt opposing behavior. Because of the potential constraints presented by the CS’s brand differentiation with the IIB, the OEM may interpret the CS’s allocation of marketing investments as an attempt to create a condition ripe for CS opportunism. For example, Wathne and Heide (2000) argue that opportunism may occur when one firm is vulnerable to another from a lock-in condition. The OEM faces a lock-in situation if the IIB designates the CS as a specified supplier. Because the CS may be reasonably expected to leverage its brand differentiation to enhance its profits (Srivastava, Shervani, and Fahey 1998) at the expense of the OEM’s profits, the OEM may seek ways to offset the CS’s brand differentiation by offsetting investments (Narasimhan et al. 2009). These investments could include creating alternative product designs that are not conducive to the CS’s product, investing in “bonding behavior” (Heide and John 1988) with the IIB, or developing a substitute product (Narasimhan et al. 2009). Second, the OEM may choose to use the relationship to its advantage. For example, it could benefit from the CS’s brand differentiation by engaging in free-riding behavior (cf. Williamson 1996). This is consistent with Dutta, Heide, and Bergen’s (1999) discussion of free-rideable services in distributor territorial arrangements and Sa Vinhas and Anderson’s (2005) conceptualization of concurrent channel free riding. Extending Jap’s (1999) argument that buyers Multidyadic Industrial Channels / 61
and suppliers may seek ways to exploit their partners’ existing synergies and idiosyncratic opportunities, we contend that the OEM may create synergies and engage in complementary activities in response to the CS’s brand differentiation. The manifestation of the OEM’s free riding and/or leveraging existing synergies is the realization of greater profits attributable to the effect(s) of the CS’s investments. Although the OEM may decide to align, oppose, or do both, it also recognizes that the benefits of these actions are constrained by uncertainty (i.e., market uncertainty and performance ambiguity). We define “OEM market uncertainty” as the OEM’s difficulty in predicting product design as required by its customer. Unlike CS market uncertainty, the OEM may view unpredictability in product design requirements with its direct customer, the IIB, as a source of costs rather than opportunity. Similarly, the OEM may view “OEM performance ambiguity” (i.e., the OEM’s difficulty in observing the installation, use, and performance assessment of its product by the IIB) as a source of costs that decreases the benefits of pursuing either strategy.
Hypotheses
Effect of Allocation of Marketing Investments on Brand Differentiation
We argue that increasing the CS’s allocation of marketing investments to the IIB positively influences its brand differentiation. The logic underlying this relationship is that such allocation facilitates an opportunity for the CS to express its value proposition to the IIB directly. Through its marketing investments (e.g., direct selling, trade shows, other marketing), the CS works to communicate that its products are of specific value to the IIB because they are rare, difficult for rivals to imitate, and impossible to substitute with products of equal quality. The extent to which the IIB recognizes value in the CS’s product results in brand differentiation, a market-based asset (Srivastava, Shervani, and Fahey 1998). Formally,
H1: The CS’s allocation of marketing investments to the IIB has a positive effect on the CS’s brand differentiation.
Effect of Brand Differentiation on CS Profits Under Uncertainty
We argue that the CS’s brand differentiation positively influences its profits. Building on the market-based asset arguments of Srivastava, Shervani, and Fahey (1998) and the concept of brand differentiation (Keller 2003), we argue that as a CS’s brand differentiation increases, the ability to leverage its brand differentiation to obtain higher profits from product sales to the OEM increases. Brand differentiation influences a firm’s profits because customers are not as willing to accept substitutes and are willing to pay higher prices (Keller 2003). As such, increased demand for the CS’s product and/or the IIB’s expressed preference for the CS’s product, stimulated by brand differentiation, signals to the OEM that the IIB’s perception of the OEM’s product is enhanced if it contains the CS’s product (“differentiation capability”; Ghosh and John 2009). However, the CS’s mar62 / Journal of Marketing, July 2014
ket uncertainty and performance ambiguity moderate this effect. First, we argue that the CS’s brand differentiation and market uncertainty interact positively to influence its profits. Increasing market uncertainty necessitates greater flexibility and responsiveness to the changing needs of the OEM and IIB (Ghosh and John 2009). Although it can introduce adaptation costs, unpredictable customer product design also increases the opportunity for the CS to distinguish its product from those of its competitors’ and to leverage its brand differentiation to gain greater profits from its OEM. For example, in conditions of design uncertainty, the CS may be able to influence the OEM’s/IIB’s design decisions in a way that suits its product offering better than its competitor’s product. Thus,
H2: As CS market uncertainty increases, the positive effect of the CS’s brand differentiation on profits increases.
Second, we argue that the CS’s brand differentiation and performance ambiguity interact negatively to influence its profits. Increasing CS performance ambiguity relative to the OEM and IIB exposes the CS to increased costs related to misdirected efforts (Ghosh and John 2009) and potential opportunism (Stump and Heide 1996). Because it is more difficult for the CS to observe the IIB’s installation and use of its product and the product’s resulting performance, the potential for downstream partners to behave opportunistically increases. As such, the costs associated with its performance ambiguity will reduce its ability to leverage its brand differentiation into profits. Formally,
H3: As CS performance ambiguity increases, the positive effect of the CS’s brand differentiation on profits decreases.
Effect of Brand Differentiation on OEM Aligning Under Uncertainty
We argue that the CS’s brand differentiation positively influences OEM aligning behavior. The logic underlying this relationship is that as the CS’s brand differentiation increases, the IIB’s preference for the CS’s product also increases. The IIB’s preference for the CS’s product signals to the OEM that the IIB’s perception of the OEM’s product is enhanced if it contains the CS’s product (i.e., differentiating capability). Thus, as the CS’s brand differentiation increases, the OEM behaves such that it leverages that brand differentiation. However, the OEM’s uncertainty (i.e., market uncertainty and performance ambiguity) moderates its behavior. First, we argue that the CS’s brand differentiation and the OEM’s market uncertainty interact negatively to influence the OEM’s aligning behavior. Increasing OEM market uncertainty exposes the OEM to increased costs of adaptation. OEMs’ products are typically the result of integrating multiple components from multiple CSs. Thus, to adapt to the IIB’s product design requirements, the OEM may be required to make substantial integration and component changes. These costs reduce the OEM’s perception of the potential profit associated with the IIB and therefore reduce its incentive to align with the CS’s brand differentiation. Thus, although the OEM may perceive the CS’s product as
providing differentiation capability, the extent to which it aligns decreases as market uncertainty increases. Therefore,
H4: As OEM market uncertainty increases, the positive effect of the CS’s brand differentiation on the OEM’s aligning behavior decreases.
Second, we argue that the CS’s brand differentiation and the OEM’s performance ambiguity interact negatively to influence the level of the OEM’s aligning behavior. Again, increasing performance ambiguity exposes the OEM to increased costs related to misdirected efforts (Ghosh and John 2009) and potential opportunism (Stump and Heide 1996). These costs reduce the OEM’s potential profit associated with the IIB and thereby reduce its incentive to align with the CS’s brand differentiation. Thus, although the OEM may perceive the CS’s product as providing differentiation capability, the extent to which it aligns decreases as performance ambiguity increases. Formally,
H5: As OEM performance ambiguity increases, the positive effect of the CS’s brand differentiation on the OEM’s aligning behavior decreases.
Effect of Brand Differentiation on OEM Opposing Under Uncertainty
We argue that the CS’s brand differentiation positively influences OEM opposing behavior. As the CS’s brand differentiation increases, the OEM’s perception of the CS’s ability to leverage its brand differentiation increases. The IIB’s expressed preference for the CS’s product also signals to the OEM that the CS may opportunistically leverage the IIB’s preference to its advantage, compelling the OEM to behave in a manner that opposes the CS’s brand differentiation (Narasimhan et al. 2009). However, the OEM’s uncertainty moderates its behavior. First, we argue that the CS’s brand differentiation interacts negatively with the OEM’s market uncertainty to influence OEM opposing behavior. Market uncertainty potentially exposes the OEM to increased adaptation costs. These costs reduce the OEM’s potential profit associated with the IIB and therefore reduce its incentive to engage in opposing behavior given the CS’s brand differentiation. As such, although the OEM may perceive the CS’s brand differentiation as potentially detrimental to its profit objectives, the extent to which it opposes the CS’s brand differentiation is reduced as its market uncertainty increases. Formally, H6: As OEM market uncertainty increases, the positive effect of the CS’s brand differentiation on the OEM’s opposing behavior decreases.
Second, we argue that the CS’s brand differentiation and the OEM’s performance ambiguity interact negatively to influence the extent of the OEM’s opposing behavior. Increasing OEM performance ambiguity exposes the OEM to higher costs related to misdirected efforts (Ghosh and John 2009) and potential opportunism (Stump and Heide 1996). These costs reduce the OEM’s potential profit associated with the IIB and thereby reduce its incentive to oppose the CS’s brand differentiation. As such, although the OEM may perceive the CS’s brand differentiation as a
threat to its own profits, the extent to which it opposes the CS’s brand differentiation decreases as OEM performance ambiguity increases. Thus,
H7: As OEM performance ambiguity increases, the positive effect of the CS’s brand differentiation on the OEM’s opposing behavior decreases.
Examining the Effects of Demand and Specification
We argue that the CS’s profits on sales to the OEM and the OEM’s behavior are related to the OEM’s perception of the CS’s brand differentiation with the IIB. Underlying this argument are two aspects of demand: change in demand for the OEM’s product and IIB’s change in product specification to the OEM involving the CS. To clarify the underlying mechanisms that may influence CS profits and OEM behavior as a result of the CS’s brand differentiation, we investigate the effects of (1) a positive change in the IIB’s demand for the OEM’s product and (2) the IIB’s expressed specification for the CS’s product.2 A positive change in the IIB’s demand is important because the OEM can view the increase as a reflection of either the CS’s brand differentiation with the IIB or its own brand differentiation with the IIB. These differences would have unique implications for whether the CS’s demand and profits are influenced as well as implications for the OEM’s behavior. The other form of demand, the IIB’s specification to use the CS’s product, is important because it may be a direct result of the CS’s brand differentiation with the IIB. Specification suggests that the CS’s product may have differentiation capability for the OEM (i.e., belief that incorporating the CS’s product enhances the IIB’s perception of the OEM’s product) (Ghosh and John 2009). This study investigates the four possible conditions that the two demand mechanisms (i.e., static demand/demand increase and no specification/CS specified) represent. In the first condition, the IIB informs the OEM that demand will be static and that it does not have a preferred or specified CS. Static demand is not necessarily a positive or negative indication of the effects of the CS’s brand differentiation. Palmatier, Gopalakrishna, and Houston (2006) note that not all business-to-business relational marketing programs are effective or produce consistent results. It may also be that the CS’s investment allocations have had a positive effect, but this effect has resulted only in retaining IIB sales (rather than increasing demand). The lack of specification suggests that the CS’s brand differentiation is not substantial. For the purpose of this analysis, this combination of demand from the IIB (i.e., status quo) serves as the baseline for comparison with the other three demand conditions. In the second condition, the IIB informs the OEM that it requires an increase in demand but does not have a preferred or specified CS. In this case, it is unclear if the increased demand is attributable to the CS’s brand differen-
2For the purposes of H –H , we do not hypothesize the effects 8 10 of market uncertainty or performance ambiguity. However, given their importance, we control for these variables when we test the hypotheses.
Multidyadic Industrial Channels / 63
tiation, the OEM’s brand differentiation, or other factors. As such, the OEM has no reason to conclude that there is a causal connection between the increase in demand for the OEM’s product and the relationship between the CS and the IIB. Furthermore, the OEM has no basis to conclude that the CS’s product possesses differentiation capability (Ghosh and John 2009) relative to the IIB. Thus, we argue that although demand for the CS’s product may increase, the CS’s profits may not change. Given the previous points, the OEM also has no incentive to alter its level of aligning with the CS’s brand differentiation. However, the increased volume combined with a lack of specification for the CS affords the OEM the opportunity to negotiate higher purchase volumes with the CS and/or seek alternative suppliers (i.e., opposing behavior). Formally,
H8: Compared with the static demand/no specification condition, an increase in demand with no specification for the CS results in (a) the same level of CS profits, (b) the same level of OEM aligning, and (c) increased OEM opposing.
In the third condition, the IIB informs the OEM that it requires no increase in demand but that it does require the OEM to use the CS’s product. In this case, the OEM has a definitive indication that the CS has established a level of brand differentiation with the IIB. In addition, because the IIB explicitly specifies the CS’s product, the OEM may conclude that the CS’s product possesses differentiation capability (Ghosh and John 2009) relative to the IIB. Because the IIB’s mandate leaves the OEM little choice but to use the CS’s product, the CS can leverage its brand differentiation to gain more favorable pricing or terms with the OEM. As such, the CS’s profits are expected to increase. Furthermore, the specification without an increase in demand would provide an incentive for the OEM to pursue additional aligning behavior to increase its gains and opposing behavior to minimize CS opportunism. Thus, H9: Compared with the static demand/no specification condition, static demand with a specification for the CS results in (a) increased CS profits, (b) increased OEM aligning, and (c) increased OEM opposing.
In the fourth condition, the IIB informs the OEM that it requires an increase in demand and that it also requires the OEM to use the CS’s product. In this condition, the OEM has an indication that the CS has substantial brand differentiation with the IIB and that the CS’s product possesses differentiation capability (Ghosh and John 2009). In light of the IIB’s mandate, any leverage gained by the OEM in relation to the CS as a result of increased demand is offset by the CS’s brand differentiation with the IIB. Thus, the CS’s profits will increase. The specification creates an incentive for the OEM to pursue additional aligning behavior. However, the increase in demand for the OEM’s product combined with a specification for the CS’s product provides no incentive for the OEM to modify its level of opposing behavior. Formally, H10: Compared with the static demand/no specification condition, increased demand with a specification for the CS results in (a) increased CS profits, (b) increased OEM aligning, and (c) the same level of OEM opposing.
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Method
To test our hypotheses, we employ a multimethod research design that incorporates two surveys (i.e., Studies 1 and 2) and an experiment (i.e., Study 3). We begin by testing the effects of a CS’s investment allocation on brand differentiation (H1) and the CS’s ability to leverage its brand differentiation to increase profits, subject to CS market uncertainty (H2) and CS performance ambiguity (H3) in a survey of CSs (Study 1). We then reexamine the effect of a CS’s investment allocation on brand differentiation (H1) in a survey of OEMs (Study 2) and examine the effects of OEM market uncertainty and OEM performance ambiguity on aligning (H4 and H5, respectively) and opposing (H6 and H7, respectively). Next, we conduct an experiment (Study 3) with OEM managers to understand the effect of demand and specification on profits, aligning behavior, and opposing behavior (H8, H9, and H10, respectively).
Studies 1 and 2
We administered two independent cross-sectional surveys. Study 1 surveyed managers at CSs, and Study 2 surveyed managers at OEMs. For both surveys, respondents were identified and incentivized by the market research firm Research Now. From the U.S. Census Bureau’s North American Industry Classification System (NAICS), we selected the following subcategories of the general manufacturing category (NAIC 33): Industrial Machinery Manufacturing (NAIC 3332), Semiconductor and Other Electronic Component Manufacturing (NAIC 3344), and Motor Vehicle Parts Manufacturing (NAIC 3363). We chose these subcategories for two reasons: (1) the industries possess a large population of CSs and OEMs serving downstream industrial buyers, which helps ensure a broad range of CS types, and (2) the end products consist of engineered systems representing the integration of specialty components and a wide range of technologies. Before survey administration, we conducted field interviews with industry managers to establish the relevance of the concepts and constructs. From these interviews and previous empirical research, we generated two survey instruments (Appendixes A and B). We pretested each survey instrument with 40 industry managers (identified through our professional network) to verify wording, response formats, and understandability. From these managers’ feedback, we finalized and formatted survey items for implementation. In two separate survey administrations, CSs and OEMs were sent an invitation to participate in an online survey. Qualification to take the survey required respondents to indicate a score of four or higher on a seven-point Likert-type scale (1 = “strongly disagree,” and 7 = “strongly agree”) regarding the extent to which they agreed with the statements “I am knowledgeable of the firm’s marketing activities” and “I am knowledgeable of the firm’s financial results.” Overall, usable surveys included responses from 156 CSs (39% response rate) and 153 OEMs (45% response rate). Table 1 lists respondent and respondent firm characteristics.
Measures
We operationalized the key study constructs using multiitem reflective scales. Respondents were asked to anchor their responses on an existing CS–OEM–IIB relationship with which their firm was currently doing business and one that was important to their firm. Table 2 provides the correlation matrix for each survey. Measures were based on existing scales when available. Likert-type scales ranged from 1 (“strongly disagree”) to 7 (“strongly agree”). “Investment allocation” reflects the CS’s percentage allocation of marketing investments to the IIB relative to the OEM. Similar to Palmatier, Gopalakrishna, and Houston’s (2006) measurement of relationship marketing expenditures, respondents estimated their allocation on a forced three-item scale that specified the percentage allocation of marketing. Respondents were asked to estimate the percentage of each of the three components (i.e., direct selling, trade shows, and other marketing) allocated to the IIB versus the OEM. “Brand differentiation” is the degree to which the CS’s product is difficult to imitate or substitute with alternative technologies or products. Modifying one of Ghosh and John’s (2009) measures for “differentiation” and two new items drawn from Srivastava, Shervani, and Fahey’s (1998) conceptualization of brand differentiation, respondents reported on the CS’s product offering with a three-item, seven-point Likert-type scale. Items assessed respondents’ relative agreement with statements describing the CS’s products as (1) difficult for competitors to imitate, (2) difficult to substitute, and (3) differentiable from competitive products. “Profits” refers to the CS’s profits on product sales to the OEM. We captured profits with a three-item, sevenpoint Likert-type scale that assessed respondents’ relative agreement with statements indicating whether (1) net profits, (2) overall profits, and (3) return on marketing investments for their firm’s product were higher with this OEM than with similar OEMs. “Aligning” involves behavior intended to leverage the effect(s) of the CS’s allocation of marketing investments. TABLE 1 Survey Data
Potential respondents Qualified respondents Completed surveys Usable surveys
CS Survey
1,096 424 39% 170 40% 156 37%
Firm size (Annual Sales in US$)
