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Purchasing Higher-Value, Higher-Price Offerings in Business MarketsJames C. Andersona; Finn Wynstraba Kellogg School of Management, Northwestern University, Evanston, IL b RSM Erasmus University,Rotterdam, The Netherlands

Online publication date: 22 February 2010

To cite this Article Anderson, James C. and Wynstra, Finn(2010) 'Purchasing Higher-Value, Higher-Price Offerings inBusiness Markets', Journal of Business-to-Business Marketing, 17: 1, 29 61To link to this Article: DOI: 10.1080/10517120903000363URL: http://dx.doi.org/10.1080/10517120903000363

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Journal of Business-to-Business Marketing, 17:2961, 2010Copyright Taylor & Francis Group, LLC ISSN: 1051-712X print/1547-0628 onlineDOI: 10.1080/10517120903000363

WBBM1051-712X1547-0628Journal of Business-to-Business Marketing, Vol. 17, No. 1, Jan 2010: pp. 00Journal of Business-to-Business Marketing

Purchasing Higher-Value, Higher-Price Offerings in Business Markets

Purchasing Higher-Value, Higher-Price Offerings in Business MarketsJ. C. Anderson and F. Wynstra

JAMES C. ANDERSONKellogg School of Management, Northwestern University, Evanston, IL

FINN WYNSTRARSM Erasmus University, Rotterdam, The Netherlands

Purpose: A conceptual framework is proposed and tested to betterunderstand customers purchase of higher-value, higher-priceofferings in business markets. Ambiguity about superior value andconsequences of obtaining superior value are the constructs in thisframework. Ambiguity about superior value is meant to capturethe concern and doubt that managers at customer firms haveabout whether their business will actually realize the cost savingsor ability to earn incremental revenue and profits that suppliersclaim for their offerings. Consequences of obtaining superior valuerefers to the outcomes that a customer manager anticipates orexperiences in making a purchase decision for higher-value,higher-price offerings.

Methodology: Two operationalizations of each construct arestudied in a pair of experiments with purchasing managers andplant maintenance managers.

Findings: Value evidence and incentive to change each receivesignificant support as mechanisms to reduce ambiguity aboutsuperior value. Notably, reference customers and pilot programsappear to be equally effective as value evidence in reducing

The authors gratefully acknowledge the financial support for the research provided byISBM. James C. Anderson also gratefully acknowledges the financial support provided by theDepartment of Technology Management, Eindhoven University of Technology, The Netherlands,where he was a visiting research professor when the research began. The comments ofAlexander Chernev and the participants at colloquia at Harvard Business School, Ohio StateUniversity, and RSM Erasmus University are gratefully acknowledged. The capable assistanceof Myungwoo Nam with the data analysis also is gratefully acknowledged.

Address correspondence to James C. Anderson, Kellogg School of Management,Northwestern University, 2001 Sheridan Road, Evanston, IL 60208. E-mail: [email protected]

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30 J. C. Anderson and F. Wynstra

ambiguity about superior value. In addition, the results providestrong empirical support that incentive to change operates as athreshold phenomenon, as predicted from social judgment theory.While no significant differences in purchase preferences are foundfor area of responsibility (purchasing versus plant maintenancemanagers), significant support is found for performance reviewand reward system as a manipulation of consequences of obtain-ing superior value.

Contribution: The conceptual framework and empirical resultssignificantly contribute to our understanding of how suppliers inbusiness markets can use monetary as well as nonmonetarymeans to persuade customers to purchase higher-value, yet higher-price offerings.

KEYWORDS business marketing, purchasing, value-based pricing,value ambiguity

It is the responsibility of marketing and sales to get an equitable or fairreturn on the value that their firms offerings deliver in business markets.When an offering delivers superior value relative to the incumbent or next-best-alternative offering, a supplier firm often would seek to claim a portionof this superior value provided by asking for a higher price relative to thatof the incumbent or next-best alternative. Although this is an essentialpart of customer value management (Anderson, Kumar, and Narus 2007;Anderson and Narus 1998), remarkably little research in business marketshas been done on understanding what would persuade business customersto purchase higher-value, yet higher-price offerings (Anderson, Thomson,and Wynstra 2000; Hkansson and Wootz 1975).

One possibility is to give customers a greater proportion of theincremental value in relation to the increase in price. But, what greater pro-portion of the incremental value needs to be given and would increasingthis proportion lead to corresponding increases in customer purchaseintentions? What other actions might a supplier take, apart from monetaryincentives, that would be effective in persuading customers to move tohigher-value, yet higher-price offerings? Finally, are there customer charac-teristics that would predispose managers at customer firms to purchasehigher-value, higher-price offerings, which astute suppliers might monitorto target the best prospects?

In this article our intention is to answer these questions and, in doingso, to make three contributions to our understanding of customers pur-chase of higher-value, higher-price offerings in business markets. First, westudy whether there is a means to significantly reduce ambiguity aboutsuperior value without requiring supplier firms to give incremental value

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Purchasing Higher-Value, Higher-Price Offerings in Business Markets 31

away. By ambiguity about superior value, we mean the doubt and concernthat customer managers have about whether they actually would realize thesuperior value that suppliers claim. Despite studying variations over fourfield experiments, Anderson, Thomson, and Wynstra (2000) were unable tofind support for supplier value guarantees as a value ambiguity reductionmechanism. Thus, whereas further investigation of supplier valueguarantees does not appear promising, finding an effective, nonmonetarymanipulation of the value ambiguity construct would make a significantcontribution to customer value management and market strategy in businessmarkets. We propose value evidence as a nonmonetary means of reducingvalue ambiguity and specifically test reference customers and pilot programsas manipulations of value evidence.

Second, we build on Anderson, Thomson, and Wynstra (2000) toextend our understanding of monetary incentives to change (to higher-value, yet higher-price offerings) as a means of reducing ambiguity aboutsuperior value. Studying three levels of incentive to change, rather than thetwo levels Anderson, Thomson, and Wynstra (2000) studied, enables us totest two competing theoretical perspectives as well as a pair of alternativethreshold effects.

Third, we attempt to enrich our understanding of purchasing higher-value, higher-price offerings further by drawing on past marketing theory(Bauer 1960; Cox 1967) to introduce another construct, consequencesof obtaining superior value, and study how operationalizations of it mayaffect customer manager purchase intentions for higher-value, higher-priceofferings.

In the following section we review past literature and develop our con-ceptual framework and research hypotheses. We then provide the researchmethodology, analyses, and results for a pair of experiments conductedwith managers. Finally, we discuss the implications of the results for theorydevelopment, managerial practice, and future research.

CONCEPTUAL FRAMEWORK AND HYPOTHESES

In studying the purchase of higher-value, higher-price offerings, we adoptthe meanings for value and price that Anderson and colleagues (Anderson,Jain, and Chintagunta 1993; Anderson and Narus 1998; Anderson, Narus,and Narayandas 2009; Anderson, Thomson, and Wynstra 2000) haveprovided. Value in business markets is the worth in monetary terms of theeconomic, technical, service, and social benefits a customer firm receives inexchange for the price it pays for a market offering (Anderson, Narus, andNarayandas 2009: 6). Benefits are net benefits, where any costs that thecustomer firm incurs in obtaining the sought benefits, apart from purchaseprice, are included. Price in business markets is what a customer firm pays a

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supplier firm for its market offering. Under these definitions, price is nota part of value, and the difference between value and price is thecustomers incentive to purchase a market offering (cf. Anderson, Narus, andNarayandas 2009).

Research on customer value in business markets has elaborated on thisconceptualization of value and contributed to our knowledge of the variousways suppliers can provide value to their customers. Menon, Homburg, andBeutin (2005) conceptualize benefits and costs separately and, further,distinguish between core and add-on benefits and between purchasingprice, acquisition costs, and operations costs. They find that each of these,with the exception of acquisition costs, is a significant antecedent of theircustomer value construct.

Ulaga and Eggert (2006) take a relationship perspective on customervalue and, based on qualitative research, conceived of nine value drivers,which they organize by value dimension (relationship benefits or costs) andby value source (core offering, sourcing process, or customer operations).For the core offering, product quality and delivery performance are thebenefits whereas direct costs (e.g., price) are the costs; for sourcing process,service support and personal interaction are the benefits whereas acquisi-tion costs (e.g., inventory) are the costs; and for customer operations, sup-plier know-how and time to market are the benefits whereas operationcosts (e.g., product costs) are the costs. They develop measures for each ofthese value drivers and empirically test their relationship with their relation-ship value construct. They find that relationship benefits have a strongerrelationship with relationship value than do relationship costs. An explana-tion that they offer for this finding is that relationship costs get a supplier onthe short list of those suppliers doing business with a customer, but it issuperior performance on the relationship benefits that win a supplier thelargest share of the customers business.

These studies by Menon, Homburg, and Beutin (2005) and Ulaga andEggert (2006) have strengthened our understanding of the concept of cus-tomer value and illuminated diverse ways that suppliers create and delivervalue to customers. The intent of these studies, however, was not to specifyhow customers translate these kinds of benefits and costs into monetaryterms nor how customers then would combine these monetary estimates ofvalue with price to make purchase decisions among alternative offerings. AsAnderson (2004) has discussed, we find a number of elements in definitionsof customer value, such as benefits and costs, which are not directly compa-rable. What is lacking is consideration of the commensurability of measure-ment units, which is essential to arrive at a meaning for customer value.One solution is to translate them all onto a common metric, preferably somemonetary unit (e.g., dollars or euros), as Anderson and colleagues haveadvocated. For the research questions that we seek to address, it is criticalto be specific about how value varies across the offerings studied and to

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make the translation into monetary terms explicit and known for ourresearch participants.

Ambiguity about Superior Value

Anderson, Thomson, and Wynstra (2000) define the construct valueambiguity to capture the greater uncertainty that managers at customerfirms have about the value an offering delivers relative to their certaintyabout its price. Even though customers may themselves conduct an analysisto assess the monetary worth of prospective offerings, the value found foreach prospective offering remains an estimate. In contrast, the price foreach offering is relatively certain. Thus, customer managers prefer thegreen money of lower-price, lower-value offerings over the gray moneyof higher-price, higher-value offerings, as long as minimum performancespecifications are met (cf. Hkansson and Wootz 1975).

Anderson, Thomson, and Wynstra (2000) demonstrate in a series ofexperiments that purchasing managers do not regard value and price as thesame, even when value is demonstrated in monetary terms, and changes invalue and price are monetarily equivalent. Drawing on reference-dependenttheory (Kahneman and Tversky 1979; Tversky and Kahneman 1991), theyoffer value ambiguity (relative to price) as the explanation for this perceiveddifference and provide empirical support for separate utility functions forvalue and price. Anderson, Thomson, and Wynstras support for separateutility functions versus a single utility function for both value and price pro-vides an elaboration of reference-dependent theory in business markets.

UNCERTAINTY AND AMBIGUITY ABOUT SUPERIOR VALUE

Einhorn and Hogarth (1985: 433) note that the literature on how peoplemake judgments under uncertainty is large, complex, and rife with contro-versy, and suggest that one reason for this controversy is that althoughthere is agreement that uncertainty is crucial factor in inference, there ismuch less agreement about its meaning and measurement. A part of thishas been the differing usage of the terms uncertainty and ambiguity. Forinstance, some researchers have used these terms interchangeably (e.g.,Camerer and Weber 1992), while others regard ambiguity as a kind ofuncertainty that is intermediate between ignorance and risk (cf. Einhorn andHogarth 1985). Thus, our intent is to be clear on the specific meaning wehave for ambiguity about superior value and to briefly provide support forthis conceptualization.

Early work in psychology on intolerance of ambiguity as a personalityvariable (Budner 1963) provides a conceptualization that is relevant to ourbusiness market context. An ambiguous situation may be defined as onewhich cannot be adequately structured or categorized by the individual

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because of the lack of sufficient cues . . . in short, situations characterizedby novelty, complexity, or insolubility (Budner 1963: 30).1 Customer man-agers attempting to evaluate a new offering that is higher in value buthigher in price relative to what they are presently purchasing would findthat their task possesses to some extent each of these characteristics ofnovelty, complexity, and insolubility.

Ambiguity about superior value is meant to capture the concern anddoubt that customer managers have about whether their business willactually realize the cost savings or ability to earn incremental revenue andprofits that suppliers claim for their offerings. Characteristics specific to thecustomers business cause differences in the value an offering delivers.Skepticism about supplier claims leads customer managers to have a down-ward bias in their beliefs about how the value that their business actuallyreceives will differ from what the supplier claims. Even if formal evaluationsare done after using the suppliers offering, which is relatively rare, they stillmay be incomplete because it is too difficult or costly to measure certainaspects of the suppliers offering relative to what the customer was previ-ously using (Ellram 1995). Apart from this, customer managers are moreaccustomed to price than they are to value, leading to comparativeignorance about value relative to price, which also should contribute toambiguity about superior value (cf. Fox and Tversky 1995; Anderson,Thomson, and Wynstra 2000).

VALUE EVIDENCE

To broaden our understanding of purchasing higher-value, higher-priceofferings in business markets, we propose value evidence as a nonmonetarymeans of reducing ambiguity about superior value. Customers can seeksubstantiation of the results of the value analysis from other sources. Seek-ing information from others who have experience with the higher-value,higher-price offerings is one way customers can reduce their uncertainty(Cox 1967). Cardozo and Cagley (1971) found that industrial purchaserswere significantly more likely to request bids from unfamiliar suppliers thatprovided more information in a supplier directory than from those thatprovided less information. One potential source of information is a list ofreference customers that the supplier provides (Salminen and Mller 2006).Reference customers are respected competitors that are already using thehigher-value, higher-price offerings and are willing to share their experi-ences. A supplier may request that its beta-test customers agree to serve asreference customers in exchange for earlier access or preferential pricing fora new, superior value offering (Frook 2001). Salminen and Mller (2006)suggest a phased approach to referencing, where suppliers carefullyestablish and maintain relations with initial, key customers that the supplierthen signals to prospective customers.

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Another source of value evidence is to conduct pilot programs at one ofthe plants in the customers manufacturing network. In this way, the cus-tomer firm can test out on a small scale whether the cost savings or greatervalue demonstrated in the value analysis actually are realized in practice.A customer firm may even designate one of the plants in its manufacturingnetwork as a demonstration plant where it assesses proposed improvementsbefore implementing them broadly (Nippon Steels Fastmet Plant startsoperation 2001). Suppliers may actively participate in and provide technicalsupport for these plant trials in exchange for the customer agreeing tobecome a reference customer. Having pilot program results that confirm thefindings of the value analysis should greatly reduce uncertainty aboutwhether a higher-value, higher-price offering will actually deliver superiorvalue in the customers operations.

Our research is the first to study reference customers versus pilot pro-grams as means of countering value ambiguity. It would seem, however,that the pilot program would provide greater value ambiguity reductionthan reference customers would because confirming results at one plantprovide customer managers with tangible evidence of the value that anoffering would deliver in their operations. Results from one of the customermanagers own plants would seem to generalize better than results from areference customer, which may have different operating conditions. There-fore, we hypothesize:

H1a: Providing value evidence for higher-value, higher-price marketofferings will have a positive effect on customer managers pur-chase intentions for them.

H1b: Providing value evidence for higher-value, higher-price marketofferings in the form of pilot-program results confirming thefindings of the value analysis will increase customer managers pur-chase intentions for them more than providing value evidence inthe form of respected reference customers use of those offerings.

INCENTIVE TO CHANGE

As an empirical demonstration of the value ambiguity construct, Andersonet al. (2000) studied incentive to change, where in one condition, purchas-ing managers received incremental value for the higher-value, higher-priceofferings. Under a reference dependent model with separate value andprice utility functions, incentive to change provides a purchasing managerwith a justification for choosing higher-value, higher-price offerings; even ifher firm does not realize all of the stated value, it will likely realize enoughto make it worthwhile (Anderson, Thomson, and Wynstra 2000: 325).

Anderson, Thomson, and Wynstra (2000) selected an incentive tochange of 7.5 percent (of the purchase price for the incumbent offering)

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based on Anderson and Naruss estimate (1999: 190), while their discussionof this concept suggests that it operates as a threshold phenomenon. Thatis, only when the magnitude of the incentive to change provided reaches anadequate level will it induce customer managers to change their purchaseintentions. Anderson, Thomson, and Wynstra (2000) provide no supportingunderlying theoretical rationale for a threshold effect, and they were not ableto empirically test for it, because they studied only a no-incentive-to-changecondition (0%) and one incentive-to-change condition (7.5%).

We study incentive to change as a second manipulation of ambiguityabout superior value and attempt to extend our understanding of it bystudying a 2.5 percent incentive to change in addition to the 0 percent (noincentive to change) and 7.5 percent incentive to change conditionsAnderson, Thomson, and Wynstra (2000) studied. There are two competingtheoretical perspectives on how customer managers will respond to this2.5 percent incentive.

Under a rational economic theoretical (utilitarian) perspective (e.g., VonNeumann and Morgenstein 1944; Mas-Colell, Whinston, and Green 1995),customer managers should view a 2.5 percent incentive to change as prefera-ble to no incentive to change (0%) and they should view a 7.5 percent incen-tive to change as preferable to a 2.5 percent incentive to change. Thistheoretical perspective would be expected to apply especially in a businessmarket setting, where customer managers would be more knowledgeableand make finer discriminations in their evaluations of new product offeringscompared with consumers (Howard 1989; Narayandas 2005; van Weele2002). As a result, we would predict significant differences in purchase inten-tions among the 0, 2.5, and 7.5 percent incentive-to-change conditions.

Social judgment theory (Sherif and Hovland 1961) provides a compet-ing theoretical perspective that would support threshold judgments. Thistheory posits that individuals making judgments about stimuli form psycho-logical scales that cannot be gauged against an objectively graded stimulusseries. Rather, reference points such as the individuals own position andother anchors lead to judgment categories against which stimuli arecompared and appraised. Two social judgment categories of interest arelatitudes of acceptance and latitudes of rejection. On a social referencescale, we may refer to the range of positions that includes an individualsstand and other positions that he will tolerate as his latitude of acceptance.Beyond this, other positions on the issue are rejected, and that range ofpositions is his latitude of rejection (Sherif and Hovland 1961: 1314).Sherif (1963) has demonstrated that the concepts of latitude of acceptanceand latitude of rejection also apply to consumer purchase decisions. Sheriffound significant differences between American Indian and nonAmericanIndian samples in their latitudes of rejection and acceptance in judging aseries of monetary values (i.e., prices) for the purchase of a warm wintercoat, providing support for social judgment theory.

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From the results of Anderson, Thomson, and Wynstra (2000), we caninfer that no incentive to change (0%) was judged by research participantsas being in their latitude of rejection, whereas a 7.5 percent incentive tochange was judged by research participants as being in their latitude ofacceptance, resulting in a significant difference in purchase intentions.The intriguing question is: How will our research participants judge a 2.5percent incentive to change? If they view it either as not different fromresearch participants receiving the 0 percent incentive to change or notdifferent from research participants receiving the 7.5 percent incentive tochange, this would provide support for a social judgment theory thresholdperspective. Thus, by adding the 2.5 percent incentive-to-change condi-tion, we are able to empirically test not only a rational economic perspec-tive versus a social judgment perspective but also a pair of alternativethreshold effects.

We predict that there will be a threshold effect, but it is difficult tospecify which one it will be. As support for the alternative thresholdeffect, social judgment research also has found that the individualsexperience with the attitudinal object or issue has a significant effect onthe thresholds and sizes of the latitudes of acceptance and rejection (cf.Sherif and Hovland 1961). The estimate Anderson and Narus (1999) pro-vide, based on qualitative research with purchasing managers, suggeststhat 2.5 percent will fall sufficiently below the research participants ownposition (57%) on incentive to change so that it will be contrasted withthis and placed in the latitude of rejection. Admittedly, this is scant evi-dence for advancing a hypothesis about which threshold effect we willfind, so we tentatively predict that the larger incentive to change will besufficient to persuade customer managers to purchase higher-value,higher-price alternatives, while the smaller incentive will not. Thus, wehypothesize:

H2a: Adding a large monetary incentive to change to the value ofhigher-value, higher-price offerings will increase customer manag-ers purchase intentions for them.

H2b: Adding a small monetary incentive to change to the value ofhigher-value, higher-price offerings will not increase customermanagers purchase intentions for them relative to when no mone-tary incentive to change is provided.

H2c: Adding a large monetary incentive to change to the value ofhigher-value, higher-price offerings will increase customermanager purchase intentions for them relative to when a smallmonetary incentive to change is provided.

If H2b is rejected, H2c enables us to test the threshold versus the rationaleconomic hypothesis.

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Consequences of Obtaining Superior Value

To enrich our understanding of customer managers purchase of higher-value, higher-price market offerings, we sought another construct thatwould contribute to a conceptual framework. Bauer and Cox (Bauer 1960;Cox 1967) have provided a venerable conceptual framework of perceivedrisk that offers a promising construct. They theorized that purchasedecisions are significantly affected by perceived risk, which is conceptual-ized as a function of two constructs, uncertainty and consequences.Uncertainty referred to the purchasers inability to assess the extent towhich different offerings fulfilled his or her performance requirements andpsychosocial preferences. Consequences referred to the seriousness of theoutcomes associated with purchasing an offering and their significance forthe purchaser. Although most research on this perceived risk framework hasbeen conducted with consumers (e.g., Cox and Rich 1964), it has beenapplied in business markets in research on purchasing managers selectionof suppliers and bids (Cardozo and Cagley 1971; Hkansson and Wootz1975).

As ambiguity can be seen as a kind of uncertainty (Ellsberg 2001, 1961;Einhorn and Hogarth 1985), and Bauer (1960) and Cox (1967) used uncer-tainty in a broad way that would include ambiguity about offerings, theconsequences of purchasing an offering would appear to be a promisingconstruct to add to a conceptual framework. Consequences of obtainingsuperior value refers to the outcomes that a customer manager anticipatesor experiences in making a purchase decision for higher-value, higher-priceofferings. McQuiston and Dickson (1991) have found that perceivedpersonal consequences have a significantly positive effect on customermanagers degree of participation and influence in the sequential phases ofan industrial purchase decision. We investigate two operationalizations ofthis construct.

AREA OF RESPONSIBILITY

Studying purchase intentions of customer managers from two areas ofresponsibility who would be expected to experience contrasting effectsfrom obtaining superior value is one operationalization of the consequencesfor obtaining superior value construct. When the higher value or lower totalcost of ownership that an offering delivers falls outside of customer manag-ers areas of responsibility, they will not directly experience the beneficialconsequences. Compounding this further, when the customer managers arein an area of responsibility in which they will experience the adverse conse-quence of paying a higher price, while customer managers in another areaof responsibility will experience the beneficial consequences, they likely willbe reluctant to purchase higher-value, higher-price offerings. For example,

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purchasing a higher-value, higher-price maintenance, repair, or operating(MRO) item, such as a replacement motor, should be a more interestingproposition for a plant maintenance manager, who will experience thelower energy and maintenance costs, than it would be for a purchasingmanager, who primarily experiences the consequence of paying a higherprice.

Hkansson and Wootz (1975: 49) found that purchasing managers weremost often unwilling to select bids for higher-quality offerings when theyhad to pay a higher price, even though the price they had to pay for thisextra quality was trifling, at most 0.4%. Their explanation for this finding,supported by discussions with purchasing managers who participated in theresearch, was that other departments, such as production, would benefitfrom the better quality, whereas purchasing would benefit from lower price.Therefore, we hypothesize:

H3: Customer managers in an area of responsibility experiencingdirectly the beneficial consequences of higher-value, higher-priceofferings have higher purchase intentions for them than customermanagers in an area of responsibility who do not experience them.

Alternatively, purchasing managers might look beyond what is best forthem personally and consider the best alternative from the wider perspectiveof their firms. This would especially be the case in firms where purchasing isseen as a strategic function in contributing to the firms competitive positionand where purchasing is truly a cross-functional process, meaning that pur-chasing managers work together with internal customers to make acquisi-tion decisions (Martin and Grbac 2003; Narasimhan and Das 2001). Underthis progressive orientation, purchasing managers would be expected toprefer higher-value, higher-price offerings even though they will not experi-ence the direct consequences of them.

PERFORMANCE REVIEW AND REWARD SYSTEM

Varying the performance review and reward system for customer managersis a second operationalization of the consequences of obtaining superiorvalue. Past research in business markets has found that performance reviewand reward systems significantly influence customer managers purchasedecisions (Dumond 1991; Qualls and Puto 1989). Anderson and Chambers(1985: 17) go as far as to declare that the reward/measurement process isthe most fundamental and enduring influence on the behavior of buyingcenter members across all types of organizational settings. Customer man-agers who are measured and rewarded for staying within the establishedbudget should seek lower-value, lower-price market offerings, as long as allof the offerings meet the minimum performance specifications. In contrast,

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customer managers who are measured and rewarded for lowering total costof ownership (Ellram 1993) or increasing the value received should be will-ing to pay a higher price to attain the higher value offerings. Thus, wehypothesize:

H4a: Performance review and reward system will have an effect on cus-tomer managers purchase intentions for higher-value, higher-pricemarket offerings.

H4b: In a scenario where a significant component of the performancereview and reward system is staying within the established budget,customer managers will have higher purchase intentions for lower-value, lower-price market offerings than in scenarios where asignificant component of the performance review and reward sys-tem is lowering total cost of ownership.

H4c: In a scenario where a significant component of the performancereview and reward system is lowering total cost of ownership,customer managers will have higher purchase intentions forhigher-value, higher-price market offerings than in scenarios wherea significant component of the performance review and rewardsystem is staying within the established budget.

METHOD

Questionnaire Development

We developed two experiments, drawing on past research and twobusiness roundtable discussions with senior purchasing executives in theNetherlands. Because the research setting was the Netherlands, these busi-ness roundtable discussions were valuable in discussing the constructs andpotential manipulations of them with purchasing executives from firms in avariety of business markets. The roundtable discussions were conducted inEnglish, enabling us not only to test wordings of the potential manipula-tions but also to understand their applicability to business markets in theNetherlands.

To manipulate the experimental factors, we constructed purchasingscenarios (e.g., Qualls and Puto 1989). Closely paralleling Anderson, Thom-son, and Wynstra (2000), the scenarios were built around the purchase of10 KW/HP replacement motors (as an MRO item). This choice of product istimely in that suppliers have begun offering lines of premium-efficiencyreplacement motors, which provide greater cost savings and have higherprices (cf. Anderson, Thomson, and Wynstra 2000). We also constructed thescenarios so that the incumbent supplier always provided the incumbent,reference offering and the alternative offerings (to remove any ambiguitycaused by having to change suppliers). To make certain that research partic-ipants understood critical terms, such as value and price, in the way that we

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were intending, we provided a cover sheet explaining the terminology inthe survey.

The different versions were then checked for factual consistencies withtwo suppliers of electric replacement motors active in the Netherlands,pretested with a number of purchasing managers who participated in theroundtable discussions, and carefully revised to reflect the managers under-standing and usage of terms and phrases (Hilton 1995). A native Dutchspeaker fluent in English translated the original English questionnaires intoDutch. To ensure accuracy, this version then was back-translated intoEnglish by another native Dutch speaker who is fluent in English. The mainbody of the scenario text appears in Appendix 1 and the inserts correspondingto the varying manipulations appear in Appendix 2.

Design of the Experiments

Experiment 1 has a 3 3 2 5 design, with the first three factors asbetween-subject factors and the fourth as a within-subject factor. Value evi-dence is studied at three levels: no stated experience; names of tworespected competitors appear on a reference list of adopters of higher-value, higher-price motors that are willing to share their experiences; andpilot program results that confirm the value analysis findings. Customerincentive to change is studied at three levels: 0 percent (no incentive),2.5 percent, and 7.5 percent of the incumbent offerings price, added asincremental value to the value estimate for the higher-value, higher-priceofferings. Research participants area of functional responsibility is studiedat two levels: purchasing manager versus plant maintenance manager. Areaof responsibility is a selection characteristic (variable), rather than a manip-ulation, so that research participants are not randomly assigned to play arole, but actually do have the area of responsibility stated.

Product offering is the within-subject factor, composed of the incum-bent, reference offering I (with a price of 1,000) and four new, alternativeofferings that each represent a monetarily equivalent, zero net change fromoffering I. Two of these are higher-value, higher-price offerings: Offering F,with a 50 higher value and price; and offering R, with a 100 higher valueand price. The remaining two are lower-value, lower-price offerings: Offer-ing L, with a 50 lower value and price; and offering W, with a 100 lowervalue and price. The varying customer incentive-to-change amounts onlyare added to Offering F and Offering R.

Experiment 2 also has a 3 3 2 5 design. The customer incentive tochange, research participants area of responsibility, and product offeringfactors remain the same as in Experiment 1. Replacing value evidence is athree-level, between-subject factor, performance review and reward system.The three levels are: the most significant component of the managers per-formance review and reward system is based on strictly staying within the

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established budget; none stated; and the most significant component of themanagers performance review and reward system is based on reducingtotal cost of ownership.

We randomly assigned participants to the between-subject conditions,except for research participants area of responsibility. In each of the twoexperiments, after reading the scenario, the participants were asked toindicate their purchase intention for each of five different offerings underconsideration on two measures. The first was a seven-point Likert scale,anchored by certainly will not buy and certainly will buy. The secondwas a likelihood of purchase measure, where they were assigned a numberbetween 0 (designated as no chance) and 100 (designated as certainpurchase) to each of the five offerings. Each respondent participated in asingle experiment.2 This ensures independence of response between thetwo experiments.

Data Collection

Our telephone-mail-telephone survey methodology included both purchas-ing and maintenance managers, all from manufacturing industries. Bothgroups are purchasing decision makers specifically for MRO items, as wassupported in our roundtable discussions.

From the professional associations of purchasing managers andmaintenance managers, we selected representatives from manufacturingand technical service industries. These customer managers were contactedby telephone, and 446 purchasing managers and 481 maintenance manag-ers expressed interest in participating. A four-page questionnaire then wassent to them. After follow-ups, 160 purchasing managers and 150 mainte-nance representatives completed usable questionnaires, leading to satisfac-tory net response rates of 35.9 percent (purchasing) and 31.2 percent(maintenance).

To check for any nonparticipant bias, we completed short telephoneinterviews with 10 nonparticipant purchasing managers and 10 nonpartici-pant plant maintenance managers on two demographic variables: jobexperience in current function and experience with participation in valueanalysis teams. Tests between participants and nonparticipants on thesevariables revealed no significant differences.

Analyses

As each experiment is a mixed design of between-subject factors and awithin-subject factor, we analyze the data using multivariate analysis of vari-ance (MANOVA). MANOVA provides a preferred analysis for mixed designsin that it makes less restrictive assumptions about the form of the dependentmeasure variance-covariance matrix than a repeated measures ANOVA

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(Iacobucci 1994). We use SAS Proc GLM to perform these analyses (Littell,Stoup, and Freund 2002). We report the test statistic based on Pillais tracebecause it has been found to be the most robust in detecting true differ-ences under various conditions (Olson 1974).

We estimate follow-up mean contrasts for each significant interactionthat we find. These contrasts enable us to determine the mean differencesthat are responsible for the overall significant effect and to test our direc-tional hypotheses.

RESULTS

We first calculated the correlation between the customer managersresponses on the two measures for each of the product offerings. ForExperiment 1, the correlations are .91, .83, .78, .88, and .91 for offerings W,L, I, F, and R, respectively (all p < .001). For Experiment 2, the correlationsare .93, .88, .82, .90, and .92 for offerings W, L, I, F, and R, respectively (allp < .001). So, to enhance reliability, we formed a composite measure of pur-chase intention and report all results for this composite measure.

Experiment 1

HYPOTHESIS 1

We find a significant value evidence by offering interaction (Pillais trace = .092,F(8, 332) = 2.00, p = .046). We depict this interaction in Figure 1, along withthe cell means. There are no significant differences between value evidenceconditions for offering W, L, and I, the two lower-price, lower-valueofferings and the incumbent offering. Supporting H1a, customer managershave significantly higher purchase intentions for offering F in the referencecustomers condition (mean purchase intention = 5.66; F(1, 185) = 8.66,p = .004) and in the pilot program confirmation condition (mean purchaseintention = 5.45; F(1, 185) = 4.24, p = .041) than in the no value evidencecondition (mean purchase intention = 4.87). And, customer managers havesignificantly higher purchase intentions for offering R in the referencecustomers (mean purchase intention = 5.15; F(1, 185) = 4.22, p = . 042) andpilot program confirmation (mean purchase intention = 5.54; F(1, 185) = 9.55,p = .002) conditions than in the no value evidence condition (mean pur-chase intention = 4.54). Finally, there is a significant main effect for valueevidence (F(2, 168) = 3.63, p = .029).

Considering H1b, we find no significant differences between customermanagers purchase intentions in the pilot program confirmation andreference customers conditions for offering F (F(1, 185) = .67, p = .415) oroffering R (F(1, 185) = 1.26, p = .263). Thus, H1b is not supported.

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HYPOTHESIS 2

We find a significant incentive to change by offering interaction (Pillaistrace = .153, F(8, 332) = 3.43, p < .001). We depict this interaction in Figure 2,along with the cell means. There are no significant differences betweenincentive to change conditions for offering W, L, and I, the two lower-price,lower-value offerings and the reference, incumbent offering. SupportingH2a, customer managers have significantly higher purchase intentions foroffering F (mean purchase intention = 5.73; F(1, 185) = 23.94, p < .001) andfor offering R (mean purchase intention = 5.31; F(1, 185) = 5.09, p = .025) inthe 7.5 percent incentive-to-change condition than in the 0 percent incen-tive to change condition (mean purchase intentions of 4.43 and 4.63,respectively). Rejecting H2b, however, we find that customer managers alsohave significantly higher purchase intentions for offering F (mean purchaseintention = 5.80; F(1, 185) = 26.07, p < .001) and for offering R (meanpurchase intention = 5.26; F(1, 185) = 4.29, p = .040) in the 2.5 percent incen-tive to change condition than in the 0 percent condition. The 2.5 percentincentive to change appears sufficient to significantly increase customermanager purchase intentions.

Considering H2c, we find no significant differences between customermanagers purchase intentions in the 7.5 and 2.5 percent incentive tochange conditions for offering F (F(1, 185) = .07, p = .788) or offeringR (F(1, 185) = .03, p = .869). Thus, H2c is not supported, suggesting that a

FIGURE 1 Experiment 1: Value Evidence by Offering Interaction.

Note. Offerings W and L are the lower-price, lower-value offerings, Offering I is the incumbent offering,and Offerings F and R are the higher-value, higher-price offerings.

0

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3

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5

6

7

W L I F R

None RC PP

Cell Means Offering

Condition W L I F R

No external validation 3.21 3.10 3.57 4.87 4.54

Reference customers 2.74 2.72 3.62 5.66 5.15

Pilot program confirmation 2.73 2.94 4.01 5.45 5.54

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2.5 percent monetary incentive to change passes a sufficient threshold level(latitude of acceptance), with the incremental 5 percent monetary incentivebetween it and the 7.5 percent condition having negligible effect.

HYPOTHESIS 3

We found no area of responsibility by offering interaction (Pillais trace = .015,F(4, 165) = .63, p = .642). Thus, H3 is not supported. There also is no maineffect for area of responsibility (F(1, 168) = .014, p = .923). Purchasing man-agers and plant maintenance managers appear to have virtually the samepurchase intentions in the various conditions.

Experiment 2

HYPOTHESIS 2

We again find a significant incentive to change by offering interaction(Pillais trace = .196, F(8, 318) = 4.32, p < .001). We depict this interaction inFigure 3, along with the cell means. Customer managers in the 2.5 percentcondition have significantly lower purchase intentions for offering W (meanpurchase intention = 2.67; F(1, 178) = 7.22, p = .008) than in the 0 percent

FIGURE 2 Experiment 1: Incentive to Change by Offering Interaction.


0

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7

W L I F R

0% 2.50% 7.50%

Cell Means Offering

Condition W L I F R

0% incentive to change 3.28 3.11 3.92 4.43 4.63

2.5% incentive to change 2.74 2.97 3.70 5.80 5.26


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incentive-to-change condition (mean purchase intention = 3.68); otherwise,there are no significant differences between incentive-to-change conditionsfor offerings W, L, and I, the two lower-price, lower-value offerings, and thereference, incumbent offering. Supporting H2a again, customer managershave significantly higher purchase intentions for offering F (mean purchaseintention = 5.37; F(1, 178) = 17.98, p < .001) and for offering R (mean pur-chase intention = 4.91; F(1, 178) = 8.24, p = . 005) in the 7.5 percent incen-tive to change condition than in the 0 percent incentive to change condition(mean purchase intentions of 4.01 and 3.92, respectively). Rejecting H2bagain, we find that customer managers also have significantly higher purchaseintentions for offering F (mean purchase intention = 5.66; F(1,178) = 26.23,p < .001) and for offering R (mean purchase intention = 4.79; F(1,178) = 5.94,p = .016) in the 2.5 percent incentive to change condition than in the 0 per-cent condition.

Considering H2c, we find no significant differences between customermanagers purchase intentions in the 7.5 and 2.5 percent incentive tochange conditions for offering F (F(1, 178) = .69, p = .407) or offering R(F(1, 178) = .22, p = .638). Thus, H2c again is not supported.

HYPOTHESIS 3

We found no area of responsibility by offering interaction (Pillais trace = .023,F(4, 158) = .93, p = .447). Thus, H3 is not supported again. We did find a

FIGURE 3 Experiment 2: Incentive to Change by Offering Interaction.


0

1

2

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5

6

7

W L I F R

0% 2.50% 7.50%

Cell Means Offering

Condition W L I F R

0% incentive to change 3.68 3.52 4.15 4.01 3.92



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main effect for area of responsibility (F(1, 161) = 4.22, p = .042). Not surpris-ingly, purchasing managers have significantly lower mean purchase inten-tions for the offerings than do plant maintenance managers (3.87 versus4.04).

HYPOTHESIS 4

Supporting H4a, we find a significant performance review and reward sys-tem by offering interaction (Pillais trace = .113, F(8, 318) = 2.38, p = .017).We depict this interaction in Figure 4, along with the cell means. Consider-ing H4b, customer managers in the stay-within-the-budget condition havesignificantly higher purchase intentions than do customer managers in thelowering-total-cost-of-ownership condition for lower-value, lower-priceofferings W (mean purchase intentions of 3.67 versus 2.44, respectively;F(1, 178) = 11.05, p = .001) and L (mean purchase intentions of 3.71 versus2.84, respectively; F(1, 178) = 7.59, p = .007). Considering H4c, customermanagers in the lowering-total-cost-of-ownership condition have signifi-cantly higher purchase intentions than do customer managers in the stay-within-the-budget condition for higher-value, higher-price offerings F (meanpurchase intentions of 5.45 versus 4.74, respectively; F(1, 178) = 4.76, p = .031)and R (mean purchase intentions of 5.08 versus 3.99, respectively; F(1, 178)= 9.84, p = .002). Thus, both H4b and H4c are supported.

FIGURE 4 Experiment 2: Performance Review and Reward System by Offering Interaction.


0

1

2

3

4

5

6

7

W L I F R

None Sw/iB LT-C-O

Cell Means Offering

Condition W L I F R

None stated 3.21 3.10 3.57 4.87 4.54

Stay within budget 3.67 3.71 4.31 4.74 3.99

Lower total cost-of-ownership 2.44 2.84 3.80 5.45 5.08

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DISCUSSION

It is crucial for the continued prosperity of suppliers in business marketsthat they get an equitable or fair return on the superior value that theirofferings deliver to targeted market segments and customer firms. Buildingon past research (Anderson, Thomson, and Wynstra 2000; Hkansson andWootz 1975), our work has made several contributions to understandingcustomer managers reluctance to purchase higher-value, higher-price offer-ings and how suppliers might persuade them to do so. We first discuss themeaning of our findings for developing a conceptual framework for under-standing the purchase of higher-value, higher-price offerings. We then dis-cuss managerial implications of our results and suggest future research.

Theory Development for the Purchase of Higher-Value, Higher-Price Offerings

The conceptual framework we have proposed and tested for understandingcustomer managers purchase of higher-value, higher-price offerings in busi-ness markets is comprised of two constructs: ambiguity about superiorvalue and consequences of obtaining superior value. We discuss in turn thecontributions of our work to a better conceptual understanding of each ofthese constructs.

AMBIGUITY ABOUT SUPERIOR VALUE

A contribution of our research has been to broaden our understanding ofthe ambiguity about superior value construct by finding an effective non-monetary means of countering it. Providing some value evidence support-ing the value estimate from the value analysis significantly increasescustomer managers purchase intentions for the higher-value, higher-priceofferings, supporting H1a. Whether this value evidence comes in the form ofa reference list containing some respected competitors that the customersare able to contact or confirming pilot program results from one of the cus-tomers own plants, it appears to allay customer managers concerns aboutwhether they will realize the stated value.

The lack of support for H1b indicates that, at least in our research set-ting, reference customers are as effective as pilot programs in significantlyreducing value ambiguity. Perhaps critical to this lack of difference was thatthe reference customers were respected competitors that the customermanager was able to contact about their experience. These descriptiveaspects of the reference customers were drawn from our business round-table discussions and pretesting of the scenarios, where participants stressedtheir importance. Given the resultant credibility of this external source,

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managers at customer firms then would be able to attribute not receivingthe stated value of the offering to their maintenance colleagues implemen-tation shortcomings rather than to a value shortfall in the offerings. Ourfindings contribute to the scant research on the use of references in busi-ness markets (Salminen and Mller 2006, 2004) and suggest more systematicstudy of references and their effects, especially as means of value evidence.

In both experiments we found strong support that adding a monetaryincentive to change to the value of higher-value, higher-price offerings willsignificantly increase customer manager purchase intentions for them. Wehave replicated the Anderson, Thomson, and Wynstra (2000) finding for0 and 7.5 percent incentive to change (H2a). We have also extended ourunderstanding of incentive to change by finding that a 2.5 percent incentiveto change also produces a significant increase in customer managerspurchase intentions for higher-value, higher-price offerings (rejecting H2b).An explanation for this may be that research participants who received the2.5 percent incentive to change viewed it as sufficiently discrepant from the0 percent incentive to change conveyed in the two lower-value, lower priceofferings (W and L) for it to be assimilated into those research participantslatitude of acceptance.

We found no support in either experiment for H2c that a 7.5 percentincentive to change would increase customer managers purchase intentionsfor higher-value, higher-price offerings significantly more than a 2.5 percentincentive to change. Providing the incremental 5 percent monetary incen-tive from the 2.5 to 7.5 percent condition had virtually no effect on cus-tomer managers purchase intentions. These findings for H2b and H2c, takentogether, provide strong empirical support that incentive to change doeswork as a threshold phenomenon in value ambiguity reduction, as pre-dicted from social judgment theory (Sherif and Hovland 1961), but that thethreshold can be much lower than previously thought. The threshold levelfor MRO offerings, such as the replacement motors in our scenarios, may belower than that for offerings that become component parts of the customersoffering, as adopting a new MRO item has much less effect on the value thata customers offerings deliver to its customers, making change less risky.The greater magnitude of the 57 percent incentive-to-change estimateoffered by Anderson and Narus (1999) may apply more to componentofferings.

CONSEQUENCES OF OBTAINING SUPERIOR VALUE

Another significant contribution of our work has been to add a secondexplanatory construct to a conceptual framework for understanding ofcustomer managers purchase of higher-value, higher-price offerings. Wehave tested area of responsibility as a selection characteristic that wehypothesized should be differentially affected by the consequences of

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obtaining superior value construct. We also have tested performance reviewand reward system as a second manifestation of the consequences ofobtaining superior value, which we actively manipulated.

We find no significant support for H3 about the effects of area ofresponsibility in either experiment. In Experiment 1, purchasing managersand plant maintenance managers purchase intentions for the variousofferings were virtually the same. In Experiment 2, although purchasingmanagers have lower purchase intentions than plant maintenance manag-ers, suggesting that they are somewhat more critical of all offerings, we findno support for our hypothesis that plant maintenance managers shouldhave higher purchase intentions than purchasing managers, specifically forthe higher-value, higher-price offerings.

A characteristic of Dutch culture is the emphasis on reaching consensusbefore proceeding with decisions, which also is pronounced in Dutch businessculture. This consensus orientation (Vossestein 2001; dIribarne 19961997)would serve to impede our area of responsibility manipulation for the con-struct consequences of obtaining superior value. Irrespective of area ofresponsibility and where the benefits would accrue, Dutch customer manag-ers would have a tendency to try to reach consensus on what they believe isbest for the firm to do. Thus, Dutch business culture theoretically would pro-vide a stringent setting for assessing the effects of area of responsibility.

Our finding of a significant interaction between performance reviewand reward system and offerings provides support for H4a. Customermanagers in the stay-within-the-budget condition have significantly higherpurchase intentions than do those in the lowering-the-total-cost-of-ownership condition for lower-price, lower-value offerings, supporting H4b.Conversely, customer managers in the lowering-total-cost-of-ownershipcondition have significantly higher purchase intentions than do those in thestay-within-the-budget condition for higher-value, higher-price offerings,supporting H4c.

Managerial Implications

An increasingly common complaint from marketing and sales managers inbusiness markets is the difficulty they have in getting a fair return on thesuperior value that their offerings deliver to present and prospective cus-tomers. Our research findings have managerial implications for suppliermanagers to accomplish getting an equitable return. We recognize,however, that care must be taken in generalizing from scenario-basedexperiments with purchasing and plant maintenance managers to actualbusiness practice in diverse business markets.

A contribution of our research, through adding the 2.5 percentcondition to the previously studied 7.5 percent condition, is the finding thatincentive to change appears to act as a threshold in the minds of customer

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managers. An implication of this is that supplier managers may be givingmore value away than is necessary. Note, however, that a critical aspect ofour research was the painstaking care we took in the scenarios to persua-sively establish the value of the alternative offerings. The scenarios estab-lished that the customer managers themselves had participated in the valueanalysis to establish the worth in monetary terms of each offering. Few sup-pliers in practice make the commitment to persuasively demonstrate anddocument the value of their offerings relative to the next-best alternatives(Anderson, Narus, and van Rossum 2006). Our findings suggest that if sup-plier managers would make this commitment, they may have to give less ofthe value away as incentive to change in negotiations with customers.

Our finding that value evidence is an effective manipulation of ambigu-ity about superior value has a couple of managerial implications. Suppliersshould conduct pilot programs with beta-test customers to understand thevalue delivered by new or enhanced offerings. The results of the pilot pro-grams, when they are carefully designed and monitored, enable the supplierto document the actual value in monetary terms that the beta customersreceive (Anderson, Narus, and Narayandas 2009). Customers may be willingto cooperate in documenting the costs savings or greater value in exchangefor supplier assistance in the data gathering and analysis as well as earlieraccess to these offerings. As further enticement, the supplier may offerexclusivity for a limited period or, when necessary, preferential pricing(Frook 2001).

Suppliers then can use the documented results to create reference cus-tomer lists and value case histories. Our finding that reference lists ofrespected competitors were as effective as confirming pilot program find-ings in persuading customer managers to have higher purchase intentionsfor higher-value, higher-price offerings suggests this two-stage strategy(Salminen and Mller 2006). Moreover, as participation in pilot programs atcustomer plants is costly and time consuming, doing this in a planned yetlimited way prior to the launch of a new or enhanced offering provides twobenefits. First, the supplier itself gains an understanding of the value thenew or enhanced offering delivers in practice. Second, it can leverage thisunderstanding through reference lists and value case histories to convey thisto prospective customer managers, potentially reducing the incentive tochange that they need to offer.

Future Research

Much research remains to be done to understand customer managers pur-chase of higher-value, higher-price market offerings. An interesting exten-sion of the value evidence manipulation for the ambiguity about superiorvalue construct would be to cross the presence and absence of referencecustomer lists with the presence and absence of pilot-program confirming

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findings. Would there be an interaction between the presentation of bothreference customer lists and pilot program results? Further, variations onreference customer lists and pilot program findings could each be assessed,such as whether the customers on the list were foreign versus domesticcompetitors (Salminen and Mller 2006) or customer lab pilot programsversus full-scale plant pilots.

Replications and extensions of our findings for the 2.5 percent incen-tive-to-change condition would be worthwhile. Future research could study2.5 percent, 7.5 percent, and a much larger incentive-to-change conditionto both replicate the 2.5 percent condition as well as to assess whether thereis an upper limit to incentive to change. Offering too large an incentive tochange may prime customers loss aversion (Tversky and Kahneman 1991),countering any value ambiguity reduction effects of incentive to change.Research in social judgment theory has found that latitudes of rejection canlie on either side of an individuals latitude of acceptance (Sherif andHovland 1961). The own-category procedure (Sherif 1963) first would beused to estimate the latitudes of acceptance and rejection for the studiedmarket offering and purchase setting. Then, a somewhat larger and a muchlarger incentive to change could be selected to test whether the somewhatlarger incentive would be assimilated into the research participants latitudesof acceptance, whereas the much larger incentive would be contrasted andplaced in their latitudes of rejection. This own-category procedure has beenapplied in marketing to estimate consumers high price and low pricethresholds for purchases (Monroe 1971).

Future research can also build our understanding of purchasing higher-value, higher-price offerings in ways that the research of Menon et al.(2005) and Ulaga and Eggert (2006) bring to mind. A change that is occur-ring in business markets is that suppliers are increasingly adding value withaugmenting services, programs, and systems. Menon et al. distinguish thesekinds of add-on benefits from core benefits. Similarly, Ulaga and Eggertstress the value that relationship benefits deliver apart from the core offer-ing. In our research, the superior value came from product performanceacore benefit. Thus, it would be worthwhile to study the effect of when thesuperior value of a higher-value, higher-price offering comes from the corebenefits versus when it comes from add-on benefits. When the superiorvalue comes from add-on benefits, does this prime customer managersambiguity about superior value more than when the superior value comesfrom the performance of the core product?

A final contribution of this research is that it might stimulate otherscholars in business marketing to take up research in understanding howsuppliers can better create, communicate, and equitably share value withcustomers. In our minds, building conceptual frameworks to understandthis and providing managerial guidance to practitioners ought to be vitaland fundamental pursuits of academic business marketing research.

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NOTES

1. Strikingly parallel to this, in early work in economics and decision theory, Ellsberg (1961: 657)speculated that ambiguity was a quality depending on the amount, type, reliability, and unanimity ofinformation.

2. To conserve research participants, who are all practitioners, we use the same purchasing man-ager and plant maintenance manager control groups for each experiment. That is, the cells where thepurchasing managers and plant maintenance managers received scenarios with no incentive to changeand no stated value evidence in Experiment 1, and no incentive to change and no stated performancereview and reward system in Experiment 2 are the same.

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APPENDIX 1: MAIN BODY SCENARIO TEXT

You have recently taken on the responsibility of purchasing motors for yourfirm. At present, your firm is purchasing 10 KW replacement motors from along-standing supplier for 1000 each. These motors are used in a widevariety of equipment in your manufacturing process. Thus, your companybuys a substantial number of these motors each year from this supplier. Atthe moment, your firm is deciding on a new standard replacement motor.This motor will be the standard for the coming years, replacing the installedbase of motors as they fail.

The supplier of replacement motors, with whom you are well-satisfied, sug-gests that you consider four alternatives in addition to the motor that yourfirm is currently using. As this supplier knows your business well, you arewilling to listen carefully to your suppliers suggestions.

The supplier shows you each motor, pointing out how the motors vary inmaintenance and energy costs. Some of the motors are premium-efficiencymotors, and will reduce your maintenance and energy costs, through lowervibration, lower temperature rise, and less downtime. The supplier alsobacks these premium-efficiency motors with the same warranty. Thedifferences in maintenance and energy costs explain the only ways thatyou will realize expected cost savings from the different motors. Althoughmaintenance and energy costs thus may differ across motors, you would notneed to retrain any personnel if you changed motors. Notice (see tablebelow) that the motors each have different acquisition prices. [Insertperformance review and reward factor level here in bold script]

In order to determine the cost savings of these four alternative motors incomparison with the incumbent motor on your manufacturing line, yourfirm has used a cross-functional team, in which you participated, to conductan internal value analysis on each of these four new motors. As part of thisvalue analysis, the team took into consideration the period of time overwhich you will realize the expected cost savings. The team has dis-counted the total expected cost savings, over the life of the motor, atyour firms cost of capital in order to express these total cost savingsin current euros. [Insert value evidence factor level here in boldscript]

Keep in mind that other than expected cost savings and acquisi-tion price, the incumbent motor and the four new motors are virtu-ally identical on everything else, including such issues as installation,availability, spare parts, and terms and conditions. The incumbentmotor and the four new motors meet your engineers minimum perfor-mance specifications. The expected life for each of the five motors is thesame, approximately 4,000 hours (1 year).

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Assume that the supplier has paid for the costs of testing these new motors.From this testing in comparison with the incumbent motor, it is clear thatany switching costs would be negligible. Please examine the descriptions ofall five motors, and then answer the following questions.

APPENDIX 2: SCENARIO INSERTS

Experiment 1: Value Evidence

Nothing Stated:

[nothing stated]

Reference Customer (RC):

In addition to this value analysis, your supplier shares with you a referencelist of customers that have started using New Motor F and New Motor R(described below), and you notice two respected competitors listed amongthe customers for each motor, which you are able to contact about theirexperience.

Pilot Program (PP):

In addition to this value analysis, your firm and the supplier have performeda pilot program together, in which New Motor F and New Motor R(described below) have been tested in one of your manufacturing plants.The results of this pilot program confirm the findings on cost savings fromthe value analysis.

Experiment 2: Performance review and reward

Nothing Stated:

[nothing stated]

Meeting the Budget (MB):

Further, the most significant component of your own performance reviewand reward plan is based on the extent to which the price paid for the

New Motor W

New Motor L

Incumbent Motor

New Motor F

New Motor R

Value relative to Incumbent Motor (over the total life)

100 lower costs

savings

50 lower costs

savings

50 higher costs

savings

100 higher costs

savings

Unit Price relative to Incumbent Motor

100 lower price

50 lower price

1000 50 higher price

100 higher price

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