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Tiger Li & Roger J. Calantone

The Impact of Market KnowledgeCompetence on New Product

Advantage: Conceptualization andEmpirical Examination

Although the role of market knowledge competence in enhancing new product advantage is assumed widely in theliterature, empirical studies are lacking because of an absence of the concept definition. In this study, the authorsconceptualize market knowledge competence as the processes that generate and integrate market knowledge. Theauthors test the conceptual mode! using data collected from the software industry. The findings show that each ofthe three processes of market knowledge competence exerts a positive influence on new product advantage. Theresults also reveal a positive association between new product advantage and product market performance. Thefindings regarding the antecedents indicate that the perceived importance of market knowledge by top manage-ment has the largest impact on the processes of market knowledge competence.

I n recent years, there has been a trend among organiza-tions to forge a linkage between markets and new prod-uct development activities. Among the most publicized

examples are the following:

• Microsoft established beta sites to seek customer knowledgein all importanl phases of new software development, fromgenerating product specifications to alpha (verifying that thesoftware conforms to specifications) and gamma (finalchecking ofthe product before its release) testitig. Micmsoflattributes Us continued market success to its vigorous pursuitof customer knowledge in new product development,

• Silicon Graphics Inc. (SGI) adopted a policy of cultivatingcustomer knowledge in its product innovation process. Whendesigning its new generation of graphics supercomputers.Onyx, SGI actively sought knowledge from heavy graphicsusers such as Walt Disney's Imagincering Group, the techni-cal producer itf Aladdin, and Coryphaeus Software, a devel-oper of space shuttle simulation software. Onyx turned out tohe one of the most popular graphics supercomputers.

• General Motors (GM) embraced the concept of competitivebenchmarking to revitalize its long-lost leadership in auto-mobile innovation. With this new thrust. GM founded theKnowledge Center in the industrial Detroit suburb of War-ren, where competitors' vehicles, from Fords to Toyotas, areexamined and studied microscopically. Although GM is a

Tiger Li is Assistant Professor of Marketing, College of Business, FloridaInternational University, Roger J. Calantone is the Eli Broad Professor ofMarketing and Product Innovation and Acting Associate Dean, Eli BroadGraduate School of Management, Michigan State University. The authorsgratefully acknowledge the funding provided by the Center for Internation-al Business Education and Research at Michigan State University. The au-thors extend sincere appreciation to S. Tamer Cavusgil, Robert W. Nason,and Bixby Cooper for their suggestions on the original research projectthat resulted in this article. They also thank Thomas Page, Bruce Seaton,Mary Jane Burns, and four anonymous JM reviewers for their helpful com-ments on the drafts of this article.

latecomer in endorsing competitive benchmarking, the com-pany quickly has made the concept an indispensable part ofits tumaround strategy.

Tbese examples, tbough notable, are representative of wbathas emerged as the major development in new product man-agement. In all cases, the company generated market knowl-edge, about eitber customers or competitors, to enbance itsnew product advantage.

Tbe etnergencc of tbis trend in new product develop-ment is not coincidental but concurrent witb a growingstream of literature in marketing tbat centers on tbe topic ofmarket knowledge competence. In his study of marketknowledge and its strategic implications, Glazer (1991) con-siders tnarket knowledge competence a strategic asset of anorganization. Hamel and Prahaiad (1994) and Sinkula(1994) consider market knowledge competence a core orga-nizational competence. Cooper (1992), Day (1994), andGriftm and Hauser (1992) propose using market knowledgecompetence to enhance new product advantage.

Althougb tbese studies bave enricbed our understandingof market knowledge competence, several issues remain un-uddressed. First, though previous researcb suggests tbatmarket knowledge competence plays an itnportant role innew product development, tbe eoncept of market knowledgecompetence bas not been defined and operationalized for-mally. Because of this gap in concept devek)pment, few em-pirical investigations bave been attempted, andconsequently, tbe impact of market knowledge competenceon new product advantage is almost undocutnented. Second.Jaworski and Kohli (1993) and Narver and Slater (1990)make a significant contribution to tnarket knowledge com-petence by capturing aspects of tbe concept with a focus oncustomer and competitor orientation. However, severalsubissues musl be addressed. Because Jaworski and Kohli(1993) were interested mainly in the overall impact of mar-ket orientation on business pertbrmance, their operational-

Journal of MarketingVol. 62 (October 1998), 13-29 Market Knowledge Competence /13

ization docs nol diffcrcnlialc between the activities of cus-tomer and competitor intormation generation, which are dis-tinct in practice. Furthermore, because Narver and Slater(1990) were facing the pioneering task of developing a mea-sure of market orientation, they include both informationprocessing and cultural norms as indicators. As a result, dif-ferentiated market information processes in new product de-velopment remain unexamincd. Third, though previousresearch {Gupta, Raj, and Wilemon 1986; Wheelwright andClark 1992) suggests that a business environment influencesorganizational behavior in new produci development, fewstudies provide empirical results regarding the effect of acompetitive environment on product innovation activities.The one exception, Olson, Walker, and Ruekert's (1995)study, examines how organizational structures influenceproduct outcomes. However, their research is confined tocoordination structures, and competitive factors, such ascustomer characteristics and technology change, are notconsidered.

We address these gaps in research by presenting andtesting a conceptual model of market knowledge compe-tence in new product development. Synthesizing marketing,business strategy, and new product developmenl literature,this study seeks answers to four primary questions: (I) Howis the concept of market knowledge competence defined andoperationalized? (2) What is the impact of market knowl-edge competence on new product advantage? (3) Does newproduct advantage enhance market performance? and (4)How do external and internal factors affect market knowl-edge competence?

Market Knowledge Competence:A Conceptual Framework

Recognizing Market Knowledge CompetenceRecognizing tbe Importance of market knowledge compe-tence is a recent pbenomenon in theory development. In neo-classical economic theory, the most important resources forproduction are labor, land, and capital. However, as informa-tion and knowledge replace matter and energy as the prima-ry resources of production (Bell 1973), neoclassical theorybecomes less tenable and is supplanted by the re source-basedtheory of the firm (Barney 1991; Conner 1991; Day 1994;Hunt and Morgan 1995), which expands the kinds of re-sources (from labor, land, and capital) to include such intan-gible ones as market knowledge competence, organizationalculture, and management skills. Tbe uncovering of marketknowledge competence as a resource is particularly signifi-cant because market knowledge competence is a "higher or-der" resource and, when harnessed, might yield competitiveadvantage (Hunt and Morgan 1995, p. 8). Although the re-source view of market knowledge competence represents anadvancement in theory development, a working definition ofthe concept is necessary for empirical examination becausetbe tertn "resource" itself is an umbrella notion that coversboth tangible and intangible assets and is not intended to con-vey the properties of market knowledge competence alone.

Defining Market Knowledge CompetenceMarket knowledge and market knowledge competence aretwo related yet separate concepts. We define market knowl-edge as organized and structured information about tbe mar-ket. Here, organized means it is the resull of systematicprocessing (as opposed to random picking), and structuredimplies ihat it is endowed with useful meaning (as opposedto discrete items of irrelevant data). We define marketknowledge competence as the processes that generate andintegrate market knowledge. Here, processes implies it is aseries of activities (as opposed to instants of thoughts). Thedistinction between the two is important for empirical stud-ies because the former is a stock, and the latter is a set ofprocesses that generate the slock. We specifically treat thelatter

Understanding competence as a series of processesstems from several studies. In his research on market-drivenorganizations. Day (1994, p. 38) defines competence as"complex bundles of skills and collective learning, exer-cised through organizational processes." In their study of thecore competencies of the corporation, Prahalad and Hamel(1990) identify a firm's processes of market interaction andfunctional integration as core organizational competencies.Furthermore, in an investigation of key issues in produci in-novation, Drucker (1985) traces a firm's competence in newproduct development to its processes of generating knowl-edge about customers and competitors and integrating suchknowledge witb tecbnology.

As a series of processes, market knowledge competenceexhibits several characteristics, including (I) inimitableness,becau.se proces.ses of generating market knowledge are em-bedded in organizational cognitive activities and are not ob-served readily from outside (Day 1994; Prabalad and Hamel1990); (2) immobility, because these processes arc createdwithin the firm and cannol be purchased in the market (Day1994); and (3) undiminishableness, because unlike ma-chines, whose value depreciates over time, the utility ofthese processes docs not diminish with usage (Prahalad andHamel 1990).

Operationalizing Market Knowledge Competence

In this research, we sugge.sl thai market knowledge compe-tence in new product development is composed of threeprocesses: (I) a customer knowledge process, (2) a com-petitor knowledge process, and (3) the marketing-researchand development (R&D) interface. A customer knowledgeprocess refers to the set of behavioral activities that gener-ates customer knowledge pertaining to customers' currentand potential needs for new products. A conipclitor knowl-edge process involves the set of bebavioral activities tbatgenerates knowledge about competitors' products andstrategies. The niarketing-R&D interface refers to theprocess in which marketing and R&D functions communi-cate and cooperate with each other.

Our operationalization is complementary to studies ofmarket orientation in .several aspects. First, anchored on thetwin domains of market orientation (customer and competi-tor orientation), the operationalization extends to include themarketing-R&D interface as a third process because of its

14 / Journal of Marketing, October 1998

role in market knowledge integration. According to market-ing-R&D interface theory (GritTin and Hauser 1992; Gupta,Raj, and Wilemon 1986; Song and Dyer 1995; Song andParry 1997), it is through the tnarketing-R&D interface thaimarket knowledge is transferred to and integrated with lech-nological knowledge. Without the interface process, themarketing and R&D functions would be segregated, result-ing in underuse of market knowledge. As Day (1991, p, 13)argues, "Market knowledge is not fully captured in a usableform until the lessons and insights are transferred beyondthose who gain the experience."

Second, though it focuses on activities in which a mar-ket-oriented UtTii engages, our operationalization is moreparsimonious because customer and competitor knowledgeprocesses are treated as two differentiable sets of behavioralactivities. When Jaworski and Kohli (1993) examined theeffects of organizational information systems in a marketorientation, they did not differentiate the behavioral activi-ties of customer and competitor information generation. Thedifferentiation is important because each set of behavioralactivities holds its own locus of interest. A customer knowl-edge process is distinct from a competitor knowledgeprocess because the customer is a separate object of percep-tion, which requires a different set of cognitive activities tolearn and understand (Day and Wensley 1983; Griffin andHauser 1991). This treatment is a priori for an empirical in-vestigation of their differentiated impacts on performance.

Third, our operationalization addresses the ambiguity ofusing both activities and culture items in measuring process-es. When Narver and Slater (1990) developed a measure ofmarket orientation, they encountered the enormous task ofintegrating both a cultural and a behavioral approach to mar-ket orientation. Consequently, some of their measures of in-formation processing were more reflective of culturalnorms. In our operationalization, we perceive marketknowledge competence as a series of organizationalprocesses that are distinct from cultural norms. This is con-sistent with a recent study by Slater and Narver (1995, p. 72)that distinguisbes organizational prtx:esses from culturalnorms and suggests that "[a]n important area for further re-search is to understand how features of the organization'sculture and climate facilitate those processes, as well as dc-tennine whether they lead to superior learning outcomes."

A Model of Market KnowledgeCompetence and New Product

AdvantageA schematic modei of market knowledge competence

and new product advantage appears in Figure I. The modelconsists of three dimensions: contributing factors to newproduct advantage, new product outcomes, and environ-mental antecedents. The model includes R&D strength as asecondary contributing factor to new product advantage be-

FIGURE 1A Model of Market Knowledge Competence and New Product Advantage

EXTERNAL

• Customerdemandingness

• Competitionintensity

• Technologychange

INTERNAL

• Perceived importanceof market knowledge

\ /

A/ \

MARKETKNOWLEDGECOMPETENCE

• Customer knowledgeprocess

•Marketing-R&Dinterface

• Competitor knowledgeprocess

• R&D strength

• New productadvantage — * • Market

performance

Antecedents Contributing Eactors Outcomes

Market Knowledge Competence /15

cause of its generally recognized role in new product devel-opment. Research and dcveiopmenl forms the cornerstoneof the traditional paradigm' for product innovation (Gal-braith 1952; Kaniicn and Schwartz 1982; Schumpeter1961). In the paradigm, new product outcomes are assumedto be dependoni on the scale of investment in R&D. Fur-thermore, Ihc Icchnology-push hypothesis (Chidamber andKon 1994; Freeman 1994), a hypothesis derived from thetraditional pariidigtii. denotes R&D strength a.s the major de-terminant of new product advantage. More recently. Day(1994) considers R&D strength a major internal capabilityand believes that strong R&D provides a technological baseindispensable lo new product development.

The proposed relationships between the components ofmarket knowledge competence and external and internal an-tecedents arc based on the principle of coalignment- be-tween organizational behavior and environment (Day andWensley 1988; Lawrence and Lorsch 1967; Venkatramanand Prescoll 1990), This principle slates thai (I) a firm'scontextual environment—whether the external environmentor inlcrnai characteristics (McKee, Varadarajan, and Pride1989)—changes over time, (2) the effectiveness ofa firm'sbehavioral processes is contingent on ihc changing environ-ment (McKce, Varadarajan, and Pride 1989), and (3) the re-sponsive level of behavioral processes has significantimplications for new product outcomes (Gupta, Raj, andWilemon 1986; Wheelwright and Clark 1992), We next de-velop and hypothesize the relationships among tbe con-structs individually.

Customer Knowiedge ProcessConsistent with organizational learning theory (Huber 1991;Sinkula 1994). we view a customer knowledge process asconsisting of three sequential aspects: customer informationacquisition, interpretation, and integration. In practice, in-formation about buyer needs for new products can be ac-quired with firm-buyer interaction activities, such as regularmeetings and discussions (Kohli and Jaworski 1990), per-sonal interviews and focus groups (Griffin and Hauser 1991;Ram 1989), and problem-solving sessions (Von Hippc!1986). Then, the obtained infortnation can be interpretedthrough various analytical procedures, such as identifying,structuring, and prioritizing needs (Griffin and Hauser 1991)and examining needs compatibility, complexity, and divisi-bility (Holak and Lehmann 1990). Finally, the analyzed in-formalion can be integrated into a new product designthrough blending techniques, such as maiching product at-tributes with needs.

'The traditional paradigm also is called tbe "SchumpeterianTbeory," customarily attributed to Schumpeter (1961) in the litera-ture but actually developed and cryslalli/cd by Galbraith (1952)and other economists. Works by Chidamber and Kon (1994). Free-man (1994). and Kamicn and Schwartz (1982) categorize studiesbased on the traditional paradigm as belonging to one of the maji>rstreams of research on product development and innovation,

-We adopt the environment —> firm behavior -> perfonnanceparadigm, as is recommended by the coalignment principle. Be-cause this principle, in general, does noi assume a direct relation-ship between environment and performance, no directrelationsbips between environmental antecedents and performancearc hypothesized.

A customer knowledge pri)cess enhances new productadvantage because it enables a firm to explore innovationopportunities created by emerging market demand and re-duce potential risks of misfitting buyer needs. Several stud-ies empirically investigate the process implementation andconsequences. In a study of 56 industrial organizations,Sanchez and Elola (1991, p. 51) fmd that certain activities ina customer knowledge process are "the most frequentmethod of finding out whether or not there is a suitable mar-ket for the new product, which correlates with ihc prepon-derance of ihe market as a source of new ideas." The authorsbelieve that these activities provide "the greatest stimulus loinnovation in the industrial firms analyzed" (p. 51). Further-more, Cooper (1992, p. 124) observes thai the process"would detennine product performance requirements andconfinn or refute that proposed feaiure.s were indeed cus-tomer benefits and of value to customers." In his research onNewProd projects involving finns in the United States.Canada, and Europe, Cooper (1992) identifies a customerknowled}>e process as a critical factor in enhancing newproduct characteristics. This leads to our first hypothesis:

H|: The more inten.se the customer knowledge process in newproduct development, the greater the new product advan-tage will be.

Marketing-R&D interfaceAs is proposed by interface theory (Griffin and Hauser1992; Gupta, Raj. and Wilemon 1986; Song and Dyer 1995;Song and Parry 1997), a bigher level of disintegration be-tween marketing and R&D functions increases the degree ofmismatch between what is needed in the market and what isdeveloped, whereas a higher level of synergy between themenhances the prospect of new prodt'.ct acceptance. In prod-uct competition, the marketing-R&D interface might deter-tnine the outcome, because a firm with better interfacing isable to realize its technological capability more efficientlythan its competition by identifying innovative product fea-tures desired by the market.

Because of its importance in new product development,the sludy of the marketing-R&D Interface has become themain thrust of a stream of literalure (Griffin and Hauser1992; Gupta, Raj. and Wilemon 1986; Mocnaert and Soud-er 1990; Song and Dyer 1995; Song and Parry 1997; Soud-er 1988). The fmdings support the proposition that theinterface enhances new product advantage. Summarizingprevious research. Griffin and Hauser (1991. p. 5) commentthat the evidence of the markcting-R&D interlace leading toproduct competiiiveness is "strong, consistent, common to avariety of methodologies, and seemingly applicable to bothservices and products and in bolh consumer and industrialmarkets." Therefore,

H2: The mt)rc intense Ihc markcting-R&D interlace in newproduct development, the greater the new product advan-tage will be.

Competitor Knowledge ProcessSimilar to a customer knowledge prt)ccss. this process alsoinvolves three behavioral aspects: ct)inpclitor informationacquisition, interpretation, and integration. According to


competitive information literature (Day and Wensley 1983,1988; Dickson 1992), a competitor knowledge process playsa significant role in diagnostic benchmarking. In a givenproduct market, firms can be classified into one of three po-sitions: inferiority, parity, or superiority. In the ftrsl case, afirm is Inferior to its competitors on key dimensions of prod-uct innovation, such as technology ownership, resource con-trol, and prtxiuct characteristics (functions, forms, andperformance). In the second case, a firm gains comparablefooting on these dimensions. In the third case, a firm is su-perior to its competilors. Generation of competitor knowl-edge is strategically importani because il provides adiagnostic framework in which a firm can benchmark its po-sition. As Day and Wensley (1988, p. I) note, "Without aproper diagnosis, managers cannot choose the best moves todefend or enhance the cunent position."

More important, a competitor knowledge process cre-ates information asymmetry between firms thai are more orless intense in implementing the process. A firm with morecompetitive information is able lo use its knowledge in sev-eral ways, including pitching its strengths against a com-petitor's weakness, internalizing a competitor's strengths byimitation, or nullifying a competitor's strengths by productdifferentiation. To emphasize the role of a competitorknowledge process, De Geus (1988, p. 74) predicts that "tbeonly competitive advantage the company of the future willhave is its managers' ability to learn [about their competi-tors] faster than [thcirl competitors." Although the idea thata competitor knowledge process strengthens competitive-ness is well conceptualized in the literature, empirical stud-ies are lacking. Therefore, we present the followinghypothesis:

HvThe more intense tbe competitor knowledge process innew product development, the greater the new productadvantage will be,

R&D StrengthResearch and development strength refers to a company'sresources and capacity for new technology development.Both the traditional economic paradigm and contemporaryresearch on new product development assume that R&Dstrength has a positive impact on new product outcomes.The economic paradigm justifies the relationship with a pro-duction function schedule. In product management studies(Hill and Sneil 1989; Szymanski, Bharadwaj, and Varadara-jan 1993), R&D strength is expected to be related positive-ly lo product advantage, because firms with greatertechnology development resources are more likely to createproducts with more innovative features.

However, research findings are mixed. In a meta-analy-sis of 76 studies (Szymanski, Bharadwaj, and Varadarajan1993), the positive impact of R&D strength is not substanti-ated. In an investigation of 122 industrial firms. Cooper(1983, p. 248) observes that R&D strength has a significanteffect on a firm's ability to produce "highly innovative andhigh-lechnology products—ones thai are mechanically andtechnically complex, affect strongly customer use behavior,and feature several differential advantages." Holak, Parry,and Song (1991) present several scenarios based on thePIMS database and show divergent effecis of R&D on out-

come measures. In general, they demonstrate that R&D ex-erts a positive impact on performance. The ambivalent re-sults from previous research make it more worthwhile toaddress the issue. Therefore,

H4: The greater the R&D strength, tbe greater tbe new productadvantage will be.

New Product AdvantagePrevious research (Calantone and Cooper 1981; Cooper1992; Crawford 1987; Edgett, Shipley, and Forbes 1992;Griffin and Hauser 1991) suggests tbal new product attrib-utes, such as new product quality, reliability, newness, anduniqueness, provide a more concrete picture ofa firm's abil-ity to meet customer needs, and "differences between alter-natives on the important attributes provide direct evidenceof advantage" (Day and Wensley 1988, p. 14),

Although quality and reliability are traditional measuresof new product advantage. Cooper (1983. p. 248) identifiesnew product uniqtteness^ as an important attribute of differ-ential advantage and reports that "programs that have a ma-jor impact on the firm involve highly innovative andhigh-technology products—ones that feature several differ-ential advantages (offer unique features to the customer andpermit ihe customer to do a unique task)." More recently.Song and Parry (1997, p, 66) review measures of productadvantage adopted in previous research and find "a signifi-cant positive relationship between tbe level of new productsuccess and measures of product competitive advantage,such as the presence of unique features, relatively high prod-uct quality, and the ability lo reduce consumer costs or en-able the consumer to perform a unique task."

New product advantage might be conelated positivelywith product market perfortnance, which refers lo the levelof financial and competitive outcomes in the market, as aredisplayed in profit, return on investment, and market share.Buyers generally form favorable perceptions of new prtxl-ucts with superior features (Carpenter and Nakamoto 1989),and they prefer such products in terms of bolh purchasepreference and actual behavior when the benefits of thesefeatures outweigh the costs (Alpert and Kamins 1995), Fur-thermore, empirical studies in new product development(Cooper 1983. 1992; Edgett, Shipley, and Forbes 1992) pro-vide some evidence that new product advantage leads to su-perior product performance. Therefore,

H : The greater the new product advantage, the better theproduct market performance will be.

External and Internal AntecedentsIn this sludy, we include four antecedents in the model, threeexternal and one internal. Customer demandingness. com-

'One reviewer suggested tbat "uniqueness" alone migbt not al-ways translate into product advantage, particularly if Ihis feature isassociated with mature products, such as mouse traps. In this study,we took several steps to avoid associating uniqueness with thistype of product. First, the product category chosen to test tbe mod-el is characterized by a high degree of product innovation. Second.the informant was requested to select an innovative new productlor evaluation. Third, six otber indicators were adopted to measureproduct advantage, in addition to uniqueness.


petition intensity, and technology change are ihe externalantecedents because ihey represent the three fundamentalforces in markets: customer, competitor, and technology(Kotler 1994). The influence of these forces on the behav-ioral activities of new product development generally isconceived of in the iiteralure; empirical validation is sparse.Perceived importance of market knowledge is an internalantecedent because of ils significance in the research agen-da. In a recent study. Slater and Narver (1995) suggest thatan important area for additional research is the invcstlgalionof how features of an organization's culture influence itsprocesses. The construct of top management's {perceptionfits this agenda because executives' mind-set is indicative ofthe cultural atmosphere in an organization.

Customer demandingness. The first antecedent that wehypothesize to have an effect on the behavioral activities ofmarket knowledge competence is customer demandingness,whicb is characterized by the level of buyers' requiretnentsfor product performance and the sophistication of their tech-nical standards and specifications. This characteristic is em-phasized by Wheelwright and Clark (1992, p. 2), whoobserve that "customers have grown more sophisticated anddemanding. Previously unheard of levels of performanceand reliability are today the expected standard. Increasingsophistication means that customers are more sensitive u>nuances and differences in a product and arc attracted loproducts thai provide solutions to their particular problemsand needs."

Several studies point to customer demandingness as amain catalyst for firms to implement processes t)f marketknowledge competence (Gupta, Raj, and Wilemon 1986;Wheelwright and Clark 1992). As customers become moredemanding, firms are prompted to intensify their activitiesand learn specific customer needs to develop needs-satisfy-ing products with superior value (Wheelwright and Clark1992). Porter (1990) offers a proaclive reason for firms tolink customer demandingness and a customer knowledgeprocess. He suggests that firms intentionally seek the mostdemanding customers as a motivating factor in tbeir pur-suance of knowledge about advanced market needs.

Furthermore, Gupta, Raj, and Wilemon (1986) suggestthat greater customer demandingness is likely to necessitategreater integration of knowledge between marketing andR&D because greater customer demandingness may signala gap between customer requirements and the product offer-ing, and such a gap can be closed only when ihe two func-tions communicate and cooperate in their informationprocessing procedures. In addition, greater customer de-mandingness may indicate that customers are not satisfiedwith existing products, which should push firms to increasetheir R&D investment and develop new products lo replacethose in the market. We therefore propose that

Hft : Tbe greater tbe customer demandingness. the moreintense the customer knowledge process in new productdevelopment will be,

Hf,!,: The greater the customer demandingness. the greater themarketing-R&D interface process in new product devel-opment will be.

Hft .: The greater tbe customer demandingness. ihe greater theR&D strength will be.

Competition intensity. Competition intensity refers tothe degree of competitive strength in a product market. AsKohli and Jaworski (1990) observe, in the absence of com-petition, monitoring competilors is not a necessity, by de-fault. However, in conditions of intensified competition,competitor inlonnalion gathering is essential for two rea-sons. First, intensified competition increases market uncer-tainty and unpredictability (Gupta, Raj, and Wilemon I9K6)and monitoring competition may help firms better anticipatechanges in competitors' new product strategies and reducemarket unpredictability. Second, with intensified competi-tion, product advantage and market share become morevolatile, and negligence of competitors may further erode afirm's market position (Day and Wensley 1988). Recentstudies in new product development (Bridges. Ensor, andThompson 1992; Song and Dyer 1995) offer empirical evi-dence in support of the view that the need for competitor in-telligence is contingent on competition intensity inhigh-lechnology firms. Stated formally,

H7: The greater the competition intensity, the more intense thecompetitor knowledge process in new product develop-ment will be.

Technologx change. Technology change refers to thespeed of technology development in a product market. Re-searchers hold ambivalent beliefs about the effect of tech-nology cbange. On the one hand. Day and Wensley (1988)and Narver and Slaler (1990) argue that, when technologyexperiences rapid change, it is imperative for firms to inter-act with customers because customer needs and preferencescan provide direction for a changing product market. On theother hand, Jaworski and Kohli (1993) suggest that, whentechnology undergoes speedy evolution, ihc importance ofcustomer infonnation generation might be diminished be-cause customers may know little about the na.sccnt technol-ogy, and therefore, close interaction with customers willprovide little insight into the emerging markets. Wilh theseconflicting arguments, an empirical investigation is neces-sary. Therefore, we propo.se the following hypothesis:

H^ : Tbe rate of technology cbange will affect the intensityof tbe customer knowledge process in new productdevelopment.

In a product market, in which technology undergoes arapid change, firms may have an urgent need to engage inintelligence gathering, because close monitoring of compe-tition provides early warnings about whether competitorscan use opportunities created by an emerging technology togain speed advantage in new product dcveiopmenl. Similar-ly, when technology experiences a shorter life cycle, firmsmust enhance their R&D strength because each technologylife cycle could squeeze those companies weak in R&D outof the served market. The formal testable hypotheses follow:

H(j[,,: The faster the rate of technology change, ibe more intensethe competitor knowledge process in new product devel-opmenl will be.

Hf( .: Tbe faster Ihe rate of technology cbange. the greater tbeR&D .strength will be.

Perceived importance of market knowledge. Top man-agement plays a key role in shaping an organization's be-havioral activities (Deshpande, Farley, and Webster 1993;

18/Journal of Marketing, October 1998

Kohli and Jaworski 1990) and providing an environmentthat is either conducive or inhibitory to behavioral process-es of market knowledge generation (Gupta, Raj, and Wile-mon 1986). Unless top managers understand and appreciatethe value ol market knowledge, the organization is unlikelyto pursue vigorously those activities that generate marketknowledge.

Jaworski and Kohli (1993) empirically find that theamount of emphasis top managers place on markei informa-tion affects a firm's generation of market intelligence aboutcompetitors and customers, as well as its interdepartmentalcoordination. The formal, testable hypotheses follow:

H9a; The greater top management's perceived importance ofmarket knowledge, the more intense the customer knowl-edge proce.ss in new product development will be.

H91,: The grcaier top management's perceived imponance ofmarket knowledge, the more intense the marketing-R&D interface in new product development will be.

Hc, .: The greater top management's perceived importance ofmarket knowledge, the more intense the competitorknowledge proces.s in new product development will be.

Relationships between the perception of market knowl-edge and R&D strength are equivocal. Tbe two constructsmay have a positive correlation wben top management be-lieves that (I) R&D strength is essential in transformingmarket knowledge into a tangible product offering and (2)the potential of market knowledge cannot be realized fullywitbout strong R&D capability. However, tbey may have anegative relationship if executives in the organization be-lieve solely in tbe idea of a technology push and ignore tbe

role of market knowledge. Consequently, executives mayoveremphasize tbe development of R&D strengtb while dis-regarding the importance of market knowledge. Therefore,we propose the following hypothesis:

H9d:Top management's perceived importance of marketknowledge affects R&D strength.

Figure 2 displays the construcls and the hypothesized rela-tionships among them.

MethodSampling Frame and SampleTbe U.S. software industry was selected to test tbe model.Tbe sampling frame was obtained from Corporate Tecbnol-ogy Infonnation Services, a company specializing in high-technology company infonnation. The frame consisted of1074 U.S. software companies and covered a wide spec-trum. The annual revenues of the firms in the samplingframe ranged from $10 million to $4 billion. The firm size,measured in number of employees, varied from 30 to morethan 40(X). The company age spanned from 5 to more than30 years.

Three waves of mailings were sent to the presidents orchief executive officers (CEOs) of the software firms in tbesampling frame. Tbe first and third consisted of question-naires, and tbe second was a postcard reminder. In addition,a telephone follow-up was conducted after the third mailing.Sixteen questionnaires were returned undelivered, and 23companies wrote or called back expressing regret at their in-

FIGURE 2A Model of Market Knowledge Competence and Hypothesized Relationships

Customerknowledge

process

Customerdemandinaness

Marketmg-R&Dinterlace

Competitionintensity

Marketperformance

New productadvantage

Com pet t torknowledge

process

Technologychange


ability to participate. During the telephone follow-up, wefurther learned tbal 82 firms did not participate because theywere software contract or consulting firms and did not de-velop their own new software products. From the remainingpool, 236 usable responses were received, whicb resulted ina 24.8% response rate. We conducted two tests to examinetbe possibility of nonresponse bias. First, we compared tbedistributions of tbe respondents in tbe sample and tbe po-tential respondents in the sampling frame. The low chi-squares and higb probabilities indicate a lack of significantdifference. Second, we compared early witb late respon-dents (AtTTistrong and Overton 1977). The first 75% of re-turned questionnaires were defined as early responses. Tbelast 25% were considered late responses and were deemedrepresentative of firms tbat did not ultimately respond to thesurvey. Tbe means ofthe eight constructs in the two groupswere compared, and no significant differences were found.Accordingly, we assume that nonresponse bias does not ap-pear to be a significant problem.

Key InformantsPresidents and CEOs were selected as tbe key informants.Althougb presidents and CEOs were used as the key infor-mants in similar research on new product development(Calantone, Vickery, and Drogc 1995), we adopted two es-tablished selection criteria in tbis study. Tbe first was posi-tion: Was the informant in a position to generalize "aboutpatterns of behavior (related to the content of inquiry], aftersummarizing eitber observed or expected organizational re-lations" (Seidler 1974. p. 817)? Presidents and CEOs ofsoftware firms were in such a position because tbey were or-ganizers of software development events and were able togeneralize patterns of tbeir firms' behavior in software de-velopment. Tbe second criterion was knowledge: Was theinformant knowledgeable about the content of inquiry? Inour pretest of nine software firms, we adopted a self-assess-ment of knowledgcability, as is suggested by Kumar, Stern,and Anderson (1993). We asked the potential informantshow knowledgeable they were about the content of inquiry.On a seven-point Likert scale (anchored at "not very knowl-edgeable'V'very knowledgeable"), the mean response was6.44 (s = .53). The mean was greater tban 5, the suggestedthreshold, tbus showing evidence of knowledgeability. Fur-thermore, presidents and CEOs were suitable for tbis studybecause a major facet of the research inquiry cut across thefunctional boundaries between marketing and R&D. Onlypersons at the top could sec the overview.

Levels of AnalysisMarket knowledge competence was assessed at tbe level ofa new product development program in an organization. Wechose the program level for two reasons. First, core compe-tence development is the task of the whole developmentprogram and sbould not be delegated to a technical team(Hamel and Prabalad 1994). Second, attributes of a firm'sproduct development program directly affect its new prod-uct outcomes (Moorman 1995). In a recetit study, Ettlie(1995) finds a close link between tbe practices of tbe devel-opment program and product performance. The measures of

the processes of market knowledge competence were indi-cated as being at the program level in tbe questionnaire.

New product outcomes were assessed at a product level.Consistent witb Moorman's (1995) and Green. Barclay, andRyans's (1995) studies, a new product in tbis researcb is de-fined as one in which there is a major functional change."* Attbe beginning of tbe questionnaire, each informant wasasked to identify a new software product tbe company's de-velopment program bad intrcxJuced into tbe U.S. market fora minimum of 12 months and a maximum of 5 years andprovide a description ofthe selected software and the indus-try tbe software served. Then the informant was requested toanswer questions using tbe selected software as a reference.

Measure Development

Measures of tbe constructs were developed in several stages.In tbe first stage, based on the defined constructs, tentativemeasures were either borrowed or developed from the exist-ing literature. In the second stage, to establish content valid-ity, a list of defined constructs and measures was submittedto a panel of five marketing, computer science, and engi-neering academicians who were recognized as authorities ontbe subject of product innovation. We requested the panelmembers to assign each measure to tbe construct tbey be-lieved was appropriate and note whether tbey thought tbeconstruct could be represented by any otber measures. In thethird stage, case study interviews were conducted for itemrefinement. In tbe interviews, executives from three select-ed software companies were asked to comment on tbe clar-ity and relevance of tbe measures, and the items wererefined accordingly. Finally, a pretest was conducted amongnine software firms.

The custotner knowledge process was measured by eigblitems on a seven-point semantic differential scale (the sev-en-poin( semantic differential was used for all subsequentitems, unless noted otherwise). Adapted from Edgett, Sbip-ley, and Forbes's (1992) and Griffin and Hauser's (1991)

^Prior research has identified three lypes ot new products: (1) in-ventive, (2) innovative, and (3) incremental. An inventive newproduct refers to a product thai is created for the inception of a newproduct category, for example, the first car with power steering(1930), television (1935), or computers (1946). An innovative newproduct is a produci with a major functional change. For example,each generation of floppy disks, that is. 8", 51^". and 31^", was con-sidered an innovative new product, relative to its predecessor, be-cau.se each involved a substanlial amount of change in accessspeed, storage capacity, and ease of use. In the software industry.Lotus Notes Is a good example of an innovative product. Althoughnetwork software products existed before its introduction, LotusNotes allowed everyone on the network to share information andbuild common databases, an important function other products didnol have. An incremental new product refers lo a produci withsome modification. Kellogg's Eggo Nutri-Grain Waffics is an ex-ample of an incremenlal new produci because ihe only "newness"of Ihc prtKiuct is increa.sed whcal grain added to the waflle. We fol-lowed two procedures to select the defined new produci. First, inthe beginning of ihe questionnaire, we instructed the respondenlthat a new software produci was a product with a major funclionalchange. Second, the respondcni was instructed to describe, in aparagraph, the new software selected. We used an industry expertto check the product descriptions and verify the produci lype.


studies, tbese items assessed the intensity of three key as-pccls of customer knowledge generation: intotTTiation acqui-sition, interpretation, and integration. Table I displays alltbe measures and tbeir sources.

Tbe markcting-R&D interface was measured using aneight-item scale. These items wore developed from prior re-search in new product dcvcloptnent (Gupta. Raj. and Wile-mon 1986; Moenaert and Souder 1990). They concentratedon (he intensity of behavioral activities of marketing-R&Dcommunication and cooperation.

The competitor knowledge process was measured usinga five-item scale adapted from Day and Wcnsley's (1988)and Dickson's (1992) studies. These items assessed the in-tensity of three aspects of behavioral activities of competi-tor knowledge generation: competitor informationacquisition, interpretation, and integration.

Research and development strengtb was measured bytbrcc items. Tbe first was the R&D expenditure in dollarsrelative to sales (Cooper 1984). The next two items askedthe infbnnant to assess the strength of the company's R&Dinvestment and proprietary technology relative to its largestcompetitor's. The two judgmental scales are rooted in PIMSstudy measures (Buzzell and Gale 1987).

New product advantage was measured by seven itemsadopled frotn two sources. Items of newness, productivity,and uniqueness were borrowed from Cooper (1983, 1992)and Cravi-ford (1987), wbo consistently identify tbcsc itemsas valid indicators of new product advantage. Items of reli-ability, compatibility, and ease of use were specific mea-sures of software product advantage. Tbey were borrowedfrom Applied Software Measurement (Jones 1991) and TotalQuality Management for Software (Scbulmcyer and Mc-Manus 1992). two widely accepted tiieasurcmcnt studies inthe industry. Together, these measures assessed a firm's newproduct advantage in relation to its largest competitor'sptt)duct using a seven-point scale ranging from 'not superi-or at all" to "extremely superior" (see Table 1).

Market performance was measured by four indicators.Following Jaworski and Kohli's (1993) work, botb judg-mental and objective measures were adopted. Two judg-mental indicators were relative intraindustry measuresborrowed from Samiee and Roth (1992). These measuresenabled the informant to a.ssess the company's softwaremarkel performance on bclore-tax profit and return on in-vestment, relative to its competition, using a five-pointscale. Each scale pt)int for the measure reflected the perfor-mance of the company in the served market within 20-per-ccntage-point intervals.-*" The objective measures were thefirm's actual dollar sbare of the served market (Buzzell andGale 1987) and pretax profit margin.

External and internal antecedetits. The three externalantecedents are customer demandingncss, competition in-tensity, and technology cbange. Customer demandingncss

•''Firms' performance on befure-tax profit was distributed as fol-lows: 14 in ihc lowest 20%, 39 in ihc luwcr-middle 20%, 66 in themiddle 20%. 70 in the upper-middle 20%. and 47 in the top 20%.In regard to return on invcstmenl. 17 firms were in the lowest 20%,39 m the lower-middle 20%;. 80 in the middle 20%. 55 in ihe up-per-middle 20%, and 45 in the lop 20%.

was measured by six items. Consistent with Wheelwrightand Clark's (1992) study, the respondents were requested toevaluate their customers' demandingness for product quali-ty, productivity, reliability, cost, service, and technical spec-ifications in comparison with other customers in tbe sameindustry. Competition intensity was measured using a four-item scale. Following Gupta, Raj, and Wilctnon's (1986)and Kohli and Jaworski's (1990) research, these items as-sessed several key features of competition in the servedmarket, including market predictability, volatility, and com-petitiveness. Technology change was measured using athree-item scale. Using the established practice in tbe soft-ware industry as a basis (Jones 1991), two items examinednew software introduction rate and product obsolescencerate (botb measured from one to seven years). The third wasa judgtnental item asking tbe informant to assess the rate oftechnology cbange using a seven-point scale that rangedfrom "slow" to "fast." The internal antecedent focused ontop management's perception of the importance of marketknowledge, and a five-item scale was adopted.

Reliability and Validity of MeasuresFollowing Gerbing and Anderson's (1988) work, v e puri-fied tbe measures by assessing tbeir reliability and unidi-mensionality. We examined the item-to-total correlations forthe items in each of the proposed scales and deleted itemswith low correlations tbat did not represent an additional do-main of interest. The last column in Table 1 presents theCronbach's alpba for each construct. An inspection ofthe al-pha coefficients reveals tbat, among tbe ten alpba coeffi-cients, nine are eitber equal to or greater tban .70, whicbindicates reliability (Nunnally 1978). The alpha coefficientlor technology change is somewbat smaller but close to thesatisfactory level of .70. Following Germain. Drogc, andDaugbcrty's (1994) suggestion, the ten constructs were sub-jected separately to principal components analyses. In eachcase, only the first eigenvalue was greater than one. whichprovides support for tbe unidimcnsionality of these scales.

To assess the discriminant validity of the subsets of mea-sures, we adopted a procedure recommended by Bagozzi.Yi, and Pbillips (1991). Witbin each subset of measures, weexamined pairs of constructs in a series of two-factor con-firmatory factor models, using EQS. For example, the set ofmeasures for a customer knowledge process was paired withthe marketing-R&D interface. We ran each model twice,once constraining tbe correlations between the two con-structs to unity and once freeing tbis parainetct. Then a cbi-squarc difference test was conducted, Tbe results indicatethat the chi-square values were significantly lower for theuticon.struincd models.^ For example, three sets of confir-matory factor models were run lor the three constructs ofmarket knowledge competence. The chi-square differencesfrom the tbree sets are 47.43. 50.21, and 82.41. respectivelyip < .01). whicb suggests that the constructs exhibit dis-criminant validity. In total, 30 tnodels were run, involving

''Because of space limits, we do not include the lengthy resultsof the discriminant validity analysis here. They can be furnished onrequest.

Market Knowtedge Competence / 21

TABLE 1Measurement Model and Confirmatory Factor Analysis by EQS

Source Constructs

EQS Item-Construct Loaditig

Standardized t-valueCronbach's

Alpha

Griffin andHauser (1991)

Edgett, Shipley,and Forbes(1992)

Jaworski andKohli (1993)

Gupta, Raj, andWilemon (1986)

Sanchez andElola (1991)


Moenaert andSouder (1990)

Griffin andHauser (1991)

Souder (1988)

Developed fromDickson (1992)

Day and Wensley(1988)

New item

Cooper (1984)

Buzzell and Gale(1987)

.92

CUSTOMER KNOWLEDGE PROCESSIn our new product development program:1. We rarely/regularly meet customers to learn their current .89

and potential needs for new products.2. Our knowledge of customer needs is scant/thorough.3. We rarely/regularly use research procedures, e.g.

personal interviews, focus groups, and surveys, to gathercustomer information.

4. We casually/systematically process and analyzecustomer information.

5. Customer information is barely/fully integrated in newsoftware design.

6. We seldom/regularly use customers to test and evaluatenew products.

7. We barely/fully understand our customers' business.8. We rarely/regularly study customers' operations for new

product development.

MARKETING-R&D INTERFACEIn our new product development program, marketing andR&D:1. Rarely/regularly communicate for new product

development.2. Rarely/regularly share information on customers.3. Rarely/regularly share information about competitors'

products and strategies, (reverse coding)4. Seldom/fully cooperate in establishing new product

development goals and priorities.5. Seldom/fully cooperate in generating and screening new

product ideas and testing concepts.6. Seldom/fully cooperate in evaluating and refining new

software.7. Are inadequately/fully represented on our product

development team, (reverse coding)8. Technological knowledge and market knowledge are

never/fully integrated in our new product development.

COMPETITOR KNOWLEDGE PROCESSIn our new product development program:1. We rarely/regularly search and collect information about

our competitors' products and strategies.2. We casually/systematically analyze information about

competitors.3. Information about competitors' products is scarcely/fully

integrated as a benchmark in our product design.4. Our knowledge of our competitors' strengths and

weaknesses is scant/thorough.5. We rarely/regularly study our competitors' software.

R&D STRENGTH1. What is your annual R&D expenditure as a percentage .88

of sales? (percentage points converted into 7-pointscale: <1%, 1-3%, 4-6%, 7-9%, 10-12%, 13-15%,> 15%)

2. How would you compare the level of your annual R&D .78expenditure with your largest competitor's? Ours is muchlower/higher.

3. How would you compare the strength of your company's .80proprietary technology with your largest competitor's?Ours is much weaker/much stronger.

.94

9883

91

93

86

9585

26.8115.51

17.37

24.40

17.67

24.5417.96

.95

9382

93

96

90

78

98

18.9913.59

21.61

21.39

16.02

11.85

27.22

.95

95

94

83

88

74

20.75

14.52

16.43

9.61

.70

12.20

12.35


TABLE 1Continued

Source Constructs

EQS Item-Construct Loading

Cronbach'sStandardized t-value Alpha

Cooper(1983,1984,1992)

Crawford (1987)Edgett, Shipley

and Forbes(1990)

Jones (1991)Cooper

(1983,1984,1992)

Crawford (1987)Jones (1991)Schulmeyer and

McManus(1992)

Robinson andPearce (1988)

Samiee and Roth(1992)

Griffin and Page(1993)

Developed fromWheelwrightand Ctark(1992)


Kohli andJaworski (1990)

Wheelwright andClark (1992)

NEW PRODUCT ADVANTAGECompared with our largest competitor's product, oursoftware is not superior at all/extremely superior:1. In terms of newness, i.e., the extent to which a product

is new to the market,2. In terms of productivity, i,e., the extent to which a

software increases a customer's work efficiency.3. In terms of reliability, i.e., the extent to which a software

is free of errors.4. In terms of compatibility i.e., the extent to which a

software is compatible with hardware and other software.5. In terms of uniqueness, i.e., the extent to which a

software has unique features.6. In terms of ease of use, i.e., the extent to which a

software is easy to learn and use.7. In terms of functionality, i.e., the extent to which a

product meets customers' functional needs.

MARKET PERFORMANCEEstimate of the market performance of this software incomparison with similar products of other firms in the samemarket, (5-point scale: lowest 20%, lower-middle 20%,middle 20%, upper-middle 20%, top 20%)1. Before-tax profit.2. Return on investment.Objective measures:3. Product market share (percentage converted into 5-point

scale: 1-5%, 6-10%, 11-15%, 16-20%, >21%),4. Pretax profit margin on this product (percentage

converted into 5-point scale: 1-5%, 6-10%, 11-15%,16-20%, >21%)

CUSTOMER DEMANDINGNESSHow would you compare your customers with othercustomers in the same industry? Our customers are:1. Less/more demanding for product quality and reliability.2. Less/more sophisticated in terms of software technical

specifications.3. Less/more sensitive to product cost.4. Less/more demanding for product service and support.5. Less/more concerned with software productivity.6. Less/more concerned with a good fit between their

needs and product offering.

COMPETITION INTENSITYHow would you describe your product market in general?This product market:1. Is predictable/unpredictable.2. Is not competitive/very competitive.3. Has stable market share/volatile market share,4. Has few new domestic competitors/many new domestic

competitors.

TECHNOLOGY CHANGE1. Rate of new software introduction instigated by

competitors: 1 to 7 years.2. Product obsolescence rate in this product market: 1 to 7

years.3. Rate of technology change in this product market:

slow/fast.

82

86

73

.77

.76

.64

.85

20.24

10.26

14.06

14.01

8.82

17.31

.92

.87

.52

16.37

6.14

14,81

9588

65887984

19.31

10.5917,1613.5313.61

88716747

.75

,58

.75

10.489.075.70

6,73

9.29

,87

.78

.85

.71

.68

Market Knowledge Competence / 23

TABLE 1Continued

Source Constructs

EQS Item-Construct Loading

Standardized t-valueCronbach's

Alpha

New item

PERCEIVED IMPORTANCE OF MARKET KNOWLEDGENot at all important/extremely important:1. Continuous interaction with users.2. Knowledge of customers' needs.3. Continuous learning of market trends and change.4. Generating competitive intelligence.5. Knowledge of competitors' products.

.92

.96

.88

.83

.84

27.1018.6211.4010.69

.87

Note: normed fit index - .99; nonnormed fit index = .99; comparative fit index = ,99.

TABLE 2Means, Standard Deviations, and Correlations of the Constructs Used in the Study

Correlations

Constructs MeanStandardDeviation '10

Customer demandingnessCompetition intensityTechnology changePerceived importanceCustomer knowledge processMarketing-R&D interfaceCompetitor knowledge processR&D strengthNew product advantageMarket performance

5.654.464.585.315.005.014.324.714.873.38

.94

.921.261.101.211.271.561.271.121.04

—.33.37.65.62.59.43.50.64.41

—.25.32.23.23.25.16.23.15

—.29.17.22.43.27.31.29

—.77.63.69.54.66.57

—.74.62.56.75.58

—.51.53.74.58

—.43.59.53

—.65.51 .62 —

15 pairs of comparison. The chi-square differenees were al!significant al p < .01.

The measures were suhjecled iurlher lo confirmatoryfactor analysis through EQS (Bentler 1989). The covarianeematrix was used as input for confirmatory factor analysis.Table 1 displays the results ofthe EQS confirmatory factoranalysis. The Bentler-Bonnet normed fit index (NFI) andnonnormed fit index (NNFI) and the comparative fil index(CFl) are .99, which indicates good fit of the confirmatorymeasurement model (Bentler 1990). In addition, the EQSconfirmatory analysis estimates ihe item-construct loadingsand t-test statistics for the measurement model. As we showin Tahle I, all the measures load significantly on their re-spective constructs at a significance level of .01, demon-strating adequate convergent validity.

Having satisfied the requiremcni arising from the mea-surement issues, we subsequently tested the structural rela-tionships using EQS path analysis (Bentler 1989). Theconstructs in the path model were represented with summat-ed scores using equally weighted scales developed from theresults of the confirmatory factor analysis.^ The correlation

matrix of the constructs appears in Tahle 2. The use of .sum-mary-item constructs is suggested by Calantone, Schmidt,and Song (1996). Cavusgil and Zou (1994), and Price,Amould, and Tierney (1995), because the method yields anacceptable variable-to-sample-size ratio and reduces themodel's complexity.

Research Findings and DiscussionThe model was tested using the Generalized Least Squaresmethod (GLS) in EQS. According to Hu and Bentler (1995),GLS has less stringent requirements for sample sizes andperforms hetter for small sample sizes (n < 250). Given thesample size of this study, GLS was the proper choice. Tahle3 presents the assessment of the model and the research hy-potheses. As we show in Table 3, the fit indices indicate anadequate fit of the model: NEI, NNFI, and CFi are .99. Theaverage standardized residual is .019. with II residualsgreater than the average. In addition, the chi-square is 26.03,with 17 degrees of freedom and .073 probability. On the ba-sis of these results, we believe ihc model fits the data well.

^Because of the complcxily und dillicully o l running a full struc-tural model, we resorted lo summated scales. Although the use ofsuminated scores enabled us to reduce model complcxily, it alsoturned our structural model into a path model with a measurement

model as a priori. The use of summaied scores represents a trade-otT. in which we gave up a full structural model fur a path model.We recognize that Ihe trade-off resulted in an attendant loss oftechnical rigor but a gain in practicality.

24/Journal of Marketing, October 1998

TABLE 3Assessment of Research Hypotheses by EQS

Constructs Hypotheses

PathCoefficient

(Standardized)Assessment

t-value

Customer knowledge process -^ New product advantageMarketing-R&D Interface -> New product advantageCompetitor knowledge process -^ New product advantageR&D strength -> New product advantage

New product advantage -^ Market performance

H,HzH3H4

H5

Customer demandingnessCustomer demandingnessCustomer demandingness

Customer knowledge processMarketing-R&D interfaceR&D strength

Competition intensity -> Competitor knowledge

Technology change -> Customer knowledge processTechnology change -» Competitor knowledge processTechnology change -> R&D strength

Perceived importance of market knowledge -* Customerknowledge process

Perceived importance of market knowledge -»Marketing-R&D interface

Perceived importance of market knowledge -* Competitorknowledge process

Perceived importance of market knowledge -* R&D strength

H

.23

.34

.20

.26

.80

.24

.34

.25

.01

-.09.26.08

.64

.40

.61

.35

4.216.724.596.37

12.68

4.264.993.19

.22

-2.385.441.45

11.40

5.86

12.43

4.59

SSSs

s

sss

n.s

n.ss

n.s

s

s

s

s'

"Two-tailed test.Note: xf,7, = 26.03; p= .073; NFI = .99; NNFI = .99; CFI - .99.

The Impact of Market Knowledge CompetenceThis research centers on the relationships between marketknowledge competence and new product advantage. As weshow in Table 3, the relationships appear to be positive, witheach component of market knowledge competence having asignificant impact (p < ,01). Acustomer knowledge proeess,as is hypothesized in H|, affects new product advantage(standardized p = .23). Hi and H3 also are supported, be-cause the marketing-R&D interface and a competitorknowledge process have positive impacts on new productadvantage (p = .34 and p = .20, respectively). These resultsprovide evidence in support of the theory that the threeprocesses of market knowledge competence are critical increating superior new products. Among the three compo-nents, the marketing-R&D interface has the largest stan-dardized coefficient and, therefore, might exert the strongestinfluence on new product advantage. As is proposed in H4.R&D strength appears to be correlated with new product ad-vantage (P = .26), which suggests that R&D in a firm playsa signifieant role in enhancing product advantage.

The ultimate goal of new product development is to im-prove market performance. As we show in Table 3, H5 issupported, with new product advantage exerting a signifi-cant influence on new product market performance (P = .80,p < .01). This finding substantiates a close linkage betweenbehavioral processes of market knowledge competence andproduct market performance and suggests that marketknowledge competence leads to better product market per-fonnanee by enhancing new product advantage.

External and Internal AntecedentsAs we indicate in Table 3, customer demandingness ap-pears to affect the intensity of both a customer knowledgeprocess (H(,y, p = .24, p < .01) and the markeling-R&D in-terface (Hftb. P = -34, p < .01). This suggests that the be-havioral activities of market knowledge eompetence areinfluenced by the characteristics of customers. This findingseems to corroborate Von Hippel's (1986) perspective oflead users. Von Hippel suggests that interaction with leadusers, defined as those customers who are more sophisti-cated and demanding than the rest of the customers in aproduct market, strengthens a firm's new product program.The relationship between customer demandingness andR&D strength is also signifieant (p = .25, p < .01), whichprovides some evidence in support of the proposition (H^^)that, when cu.stomers are more demanding, a firm is morelikely to strengthen its R&D.

The relationship (H7) between competition intensity anda competitor knowledge process is not significant. To someextent, this finding corroborates studies by Jaworski andKohli (1993) and Slater and Narver (1994), who find that acompetitive environment does not have a direct effect on afirm's behavioral activities. However, il is possible thatcompetition intensity is a eonstruct that moderates the rela-tionship between a competitor knowledge process and newproduct advantage.

Technology change does not have a significant impacton the intensity of a eustomer knowledge process (Hg^).However, the relationship between technology change and


the intensity of a competitor knowledge pUK'ess is signifi-canlly positive {H^^. p = .26, p < .01). which indicates that,when a product's life cycle shortens, fimis are more likely tointensify their competitor intelligence activities. Thi.s find-ing also may suggest that, in an intense environment of tech-nology competition, companies might simplify their task byfoeusing on key competitors.

H c is not supported, which suggests that it may not becommon practice for firms to increase their R&D invest-ment in a market that experiences rapid technology change.Firms might believe it risky to increase R&D investment ina technologically uncertain market.

Finally, Hy^-Hyj are supported, with top management'sperceived importance of market knowledge exerting a sig-nificant, positive influence on the three constructs of marketknowledge competence and R&D strength. An inspection ofthe standardized coefficients shows that the correlations be-tween top management perception and these constructs aregreater than .30. The strong correlations suggest that behav-ioral activities in new product development are associatedclosely with executives' philosophical thinking.

Implications and DiscussionManagerial ImplicationsThis study offers several guidelines for practitioners to de-velop market knowledge competence. First, our findingsshow thai market knowledge competence consists of multi-ple proces.ses, and each process has an impact on new prod-uct advantage. This underlines the necessity of including acomplete set of the processes in new product development.Although many firms realize the importance of generatingmarket knowledge, there is a tendency among managers tooveremphasize one process while ignoring others (Day andWensley I9SS). For example, a firm overvaluing the needfor a customer knowledge process might exclude a competi-tor knowledge process, or vice versa. Such an imbalancedpractice might result in fragmentary market knowledge andweaken the effectiveness of a knowledge generation system.Second, we demonstrate that the three processes of marketknowledge competence are distinct constructs with uniquefunctions. This underscores the importance of process dif-ferentiation. Because the customer and the eompetitor areseparate objects of perception, firms must use different setsof cognitive activities to learn about and understand them.Furthermore, process differentiation enables employees toacquire the expertise required by each process and increaseprocess productivity. Third, the results show that the threeprocesses cast different levels of influence on new productadvantage, with the marketing-R&D interface exerting thegreatest intluence. This highlights the importance of processprioritization. A firm should prioritize the three processesaccording to their contributions to product advantages andthen use this priority list to determine resource allocation.Process prioritization enables a firm to make efficient use ofits resources and fully realize the process potentials.

The findings pertaining to customer characteristics im-plicate customer interaction in new product deveiopment.Our research shows that customer characteristics, such as

demandingne.ss and sophistication, are correlated positivelywith the intensity of a cu.stomer knowledge process. There-fore, it is beneficial for finns to treat customers with thesecharacteristics as partners in new product development. Aspartners, their role is not hmited to voicing needs. They canhelp crystallize product concepts and critically evaluateproduct designs and final offerings. The linkage betweencustomer characteristics and the marketing-R&D interfacesuggests a constructive role for this customer group. As par-ticipants, they can facilitate the interface process. Interfunc-tional conflict arising from different opinions about productsolution is a prominent issue in the marketing-R&D inter-face (Gupta, Raj, and Wilemon 1986). Customers who areknowledgeable and articulate can help reconcile the differ-ences between the two functions by expressing their uniqueuser perspectives. Moreover, their involvement can stimu-late the interfunctional communication because they bringfresh ideas and pointed opinions to the process. Customercharacteristics also have significant implications for tech-nology development. Technology selection is a crucial issuein technology development {Wheelwright and Clark 1992).Improper selection inevitably drains R&D investment andefforts. Involving informed customers to assess technologyfeasibility might be a prudent decision in reducing invest-ment risk.

This study offers critical insights to competence choice.The debate among practitioners about competence develop-ment often treats a market knowledge competence and atechnology competence as two exclusive capabilities. Forexample, Chidamber and Kon (1994) find that decisionmakers often post competence selection as an either/or ques-tion. In this research, we demonstrate that both marketknowledge competence and R&D strength contribute to newproduct advantage. This underscores the importance ofadopting a comprehensive view. According to Day (1994),each type of competence has a unique function. Marketknowledge competence is an external capability that links afirm with the market; technology development is an internalcapability that sustains a firm's market position. Therefore,companies cannot afford to take an exclusive position. Theexclusive view of competence choice can he attributed tothe diverse professional backgrounds of decision makersand to interdepartmental conflicts (Chidamber and Kon1994). Although sueh a view might enhance the relative po-sition of a department in regard to resource allocation, it willdo so by sacrificing the overall product competitiveness ofan organization.

Scholarly Implications and Further ResearchIn this study, we advance research on market knowledgecompetence in new product development in two importantaspects. First, we develop a eonceptual framework to definethe concept of market knowledge competence. Second, wevalidate our conceptualization using data collected from thesoftware industry. Our study also offers significant implica-tions in several other areas.

The first area is development cycle time. Recently, Windand Mahajan (1997) identified cycle time reduction as oneof the key issues in new product development. We believethat our findings lay the groundwork for further research on


dcveiopmenl cycle time. We speculate that the constructs ofmarket knowledge competence may affect development cy-ele time. A customer knowledge process may help shortencycle time. In today's market, customer preferences canchange rapidly with new developments in technology. Forexample, the invention of high-definition television and itsavailability changed, almost overnight, the expectations ofhigh-end users of television products everywhere. A cus-tomer leaming process may offer firms a solution to thechanging markets by collecting and processing informationon a concurrent basis. Alternatively, a competitor knowl-edge process may reduce cycle time by promptly generatinginfonnation about competitors' development speed and en-try intentions. In a elose race, such knowledge can be usedas a stimulus to motivate employees to beat the competition.

A second area relates to the first-mover issue. The studyof the first mover centers on the performances of those com-panies that achieve the shortest time to market. However,the findings of previous research (Kerin. Varadarajan, andPeterson 1992) suggest that getting to market first does notnecessarily ensure first-mover gains. Although some com-panies succeed in translating the lead in time into a lead inmarket share and profits, others fail to do so. An applicationof the concept of market knowledge eompetence will pro-vide valuable insights into the performance di.screpancies.Specifically, the processes of market knowledge compe-tence may play a role in moderating the relationships be-tween lead time and performance. We speculate that, amongthe first movers, those that are more adept at generatingmarket knowledge will be able to achieve better perfor-mance because ihey will have better access to informationabout customer preferences for product quality and other at-tributes that are conducive to market acceptance. As Windand Mahajan (1997, p. 4) predict, the real challenge is nothow to gain lead time but "how to do so without negativelyaffecting the quality of the product." An integration of mar-ket knowledge eompetence with the first-mover issue willhelp identify those finns that are more likely to meet thechallenge, as well as demonstrate how they will do so.

A third area pertains to the implications of other mea-sures of product performance. In this research, performancemeasures are confined to market indicators; measures ofperceived success and failure are not included. Additionalresearch could extend this study by designing measures thatlink a firm's perceived success and failure with its productmarket performance. For example, in this study we askedfirms to estimate their product performance against theircompetitors'. A future study eould request firms to assesstheir market performance relative to their expectations. Fur-thermore, additional research could employ time as a crite-rion, because duration can be a significant indicator ofsuccess.

The last research area is process management. In this re-search, though we investigate the impact of the processes ofmarket knowledge competence, we do not examine howthese processes are managed. There are three major man-agement issues. The first is top management's involvement.Top management might be involved in different stages ofprocess development, including process design, implemen-tation, and maintenance. What are the relationships betweenthe extent of such involvement and the process effective-ness? Does top management's participation in the processesimprove product performance? The second issue is organi-zational mechanisms. The processes of market knowledgecompetence exist in certain organizational mechanisms. Forexample, the marketing-R&D interface can be implementedby joint committees and project teams. What other mecha-nisms are involved? Does the choice of organizationalmechanisms have an effect on these processes? The third is-sue is the evaluation and reward system. Process effective-ness depends on participants' perfonnance. What measurescurrently are adopted by organizations to evaluate employ-ees' performanee in these processes? Presumably, there is aconnection between participants' performance in theprocesses and product market outcomes. Does the evalua-tion system reeognize this linkage? An investigation of thesequestions will elevate researeh of market knowledge com-petence to a new altitude.

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