Value, Rareness and Competitive Advantage.pdf

Strategic Management JournalStrat. Mgmt. J., 29: 745–768 (2008)

Published online 23 April 2008 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/smj.686

Received 23 May 2005; Final revision received 16 January 2008

VALUE, RARENESS, COMPETITIVE ADVANTAGE,AND PERFORMANCE: A CONCEPTUAL-LEVELEMPIRICAL INVESTIGATION OF THERESOURCE-BASED VIEW OF THE FIRM

SCOTT L. NEWBERT*Villanova School of Business, Villanova University, Villanova, Pennsylvania, U.S.A.

The resource-based view of the firm (RBV) hypothesizes that the exploitation of valuable,rare resources and capabilities contributes to a firm’s competitive advantage, which in turncontributes to its performance. Despite this notion, few empirical studies test these hypothesesat the conceptual level. In response to this gap, this study empirically examines the relationshipsbetween value, rareness, competitive advantage, and performance. The results suggest that valueand rareness are related to competitive advantage, that competitive advantage is related toperformance, and that competitive advantage mediates the rareness-performance relationship.These findings have important academic and practitioner implications which are then discussed.Copyright 2008 John Wiley & Sons, Ltd.

INTRODUCTION

The resource-based view of the firm (RBV)assumes that resources, or ‘stocks of available fac-tors that are owned or controlled by the firm’ (Amitand Schoemaker, 1993: 35), and capabilities, orthe ‘firm’s capacity to deploy Resources’ (Amitand Schoemaker, 1993: 35, emphasis in original),are both heterogeneously distributed among firmsand imperfectly mobile. These assumptions allownot only for the existence of differences in firmresource endowments, but also for these differ-ences to persist over time (Barney, 1991). Basedon these assumptions, RBV scholars hypothesizethat (1) if a firm possesses and exploits resourcesand capabilities that are both valuable and rare,it will attain a competitive advantage, (2) if these

Keywords: competitive advantage; performance; rareness;resource-based view (RBV); resource-capability combi-nation; value*Correspondence to: Scott L. Newbert, Villanova School ofBusiness, Villanova University, 800 Lancaster Avenue, Vil-lanova, PA 19085, U.S.A. E-mail: [email protected]

resources and capabilities are also both inim-itable and non-substitutable, the firm will sustainthis advantage, and (3) the attainment of suchadvantages will enable the firm to improve itsshort-term and long-term performance (Amit andSchoemaker, 1993; Barney, 1991, 1997; Eisen-hardt and Martin, 2000; Henderson and Cockburn,1994; Powell, 2001; Teece, Pisano, and Shuen,1997).

In order to test these hypotheses, most scholarshave employed a ‘resource heterogeneityapproach,’ whereby a specific resource or capa-bility is argued to be valuable, rare, inimitable,and/or non-substitutable, and then the amount ofthat resource or capability possessed by a firm iscorrelated with its competitive advantage or per-formance (Newbert, 2007). Clearly, evidence thata specific resource or capability may enable a firmto attain a competitive advantage in a particularindustry setting is important given that it providesmanagers operating in that context the incentiveand justification to obtain and exploit it. Yet, itis precisely this degree of specificity that is this

Copyright 2008 John Wiley & Sons, Ltd.

746 S. L. Newbert

methodological design’s greatest limitation. Con-sider, for example, that all firms in an industrydo not (both by ability and by choice) competeon the same bases. Rolex and Timex have bothachieved tremendous success making timepieceswhile employing entirely different business mod-els. Whereas Rolex competes on quality, status,and marketing, Timex competes primarily on scale(Barney, 1997: 148). Therefore, although a spe-cific resource or capability may be found to exhibita strong correlation with competitive advantageand/or performance in a particular context, thatresource or capability may simply not fit with theenterprise-level strategies of all firms operating inthat context. For managers of those firms whoendeavor to compete on alternative bases, there islittle to be gleaned from findings of this sort.

What might be more useful to these man-agers would be findings that allowed them toautonomously identify, and in turn seek out andexploit, resources and capabilities that might notonly contribute to their firms’ competitive posi-tion, but also fit with their idiosyncratic busi-ness models. One way to arrive at such find-ings is by eschewing the tendency to predeter-mine which resources and capabilities ought tobe correlated with competitive advantage and/orperformance, and instead identify which charac-teristics of resources and capabilities are relatedto these ends. Scholars employing such a method-ological design, referred to as a ‘conceptual-levelapproach,’ typically operationalize the independentvariable not in terms of specific resources or capa-bilities, but rather in terms of their value, rareness,inimitability, and/or non-substitutability (Newbert,2007). Findings from conceptual-level studies areimportant as they provide insight into the charac-teristics that resources and capabilities in generalmust possess in order to improve a firm’s compet-itive position.

To illustrate the importance that findings of thissort might offer, consider, for example, Hendersonand Cockburn’s (1994) seminal study of pharma-ceutical firms. Employing a resource heterogeneityapproach, Henderson and Cockburn (1994) arguethat organizational competence (operationalized asthe total number of patents generated by and theimportance of publications for promotion withinthe firm) is a valuable, rare resource and find thatit is significantly related to competitive advan-tage. Although the results of this study clearly

demonstrate the significance of patents and publi-cations to success in the pharmaceutical industry,because the independent variable is operationalizedas a specific resource rather than as that resource’svalue and rareness, Henderson and Cockburn’s(1994) study is not informative with respect to pre-cisely why patents and publications are important.While one might speculate that they owe their sig-nificance to their inherent value and rareness, suchcannot be concluded with any degree of certainty.In fact, it may be that the significance of patentsand publications to a firm’s competitive advan-tage is a function of some other characteristic notaddressed by Henderson and Cockburn (1994).

Indeed, Collis and Montgomery (1995) arguethat a firm’s competitive advantage is a func-tion not only of the value, inimitability, andnon-substitutability of its resources and capabil-ities (indicative of traditional RBV logic), butalso of their durability, appropriability, and supe-riority. When applied to Henderson and Cock-burn’s (1994) findings, Collis and Montgomery’s(1995) framework suggests that the reason patents,for example, may enable pharmaceutical firms toattain a competitive advantage is because they aredurable (they offer protection for up to 20 years),appropriable (they are legally bound to the firm),and superior (they offer greater security than otherforms of intellectual property protection).

Therefore, to conclude that organizational com-petence is valuable and rare simply because it isrelated to competitive advantage is to assume thatthe RBV hypotheses linking value and rarenessto competitive advantage are factual and requireno empirical confirmation. These hypotheses, how-ever, are purely theoretical, or synthetic, andcan only be known to be true after empiri-cal investigation (Priem and Butler, 2001a). Inorder to truly understand why a resource or capa-bility contributes to a firm’s competitive posi-tion, its underlying characteristics must be exam-ined. Without such conceptual-level investigation,advice to practitioners to seek out and exploitvaluable, rare, inimitable, and/or non-substitutableresources and capabilities may be unfounded. Forexample, Markman, Espina, and Phan (2004), intheir conceptual-level study, find that competitiveadvantage in the pharmaceutical industry is relatedto the inimitability but not the substitutability ofpatents. Such results suggest that the RBV hypoth-esis relating non-substitutability and competitive

Copyright 2008 John Wiley & Sons, Ltd. Strat. Mgmt. J., 29: 745–768 (2008)DOI: 10.1002/smj

Conceptual-Level Test of the RBV 747

advantage may be invalid and hints at the possi-bility that the criteria by which managers shouldevaluate resources and capabilities may need revi-sion.

Given the insights to be gleaned from concep-tual-level studies, it is unfortunate that there is apaucity of research employing this methodologicalapproach, particularly with respect to the charac-teristics of value and rareness (Newbert, 2007).In response to this gap, this study will employa conceptual-level approach in testing the RBVhypotheses relating value and rareness to com-petitive advantage and performance. It is hopedthat the subsequent empirical results will add toour understanding regarding whether and to whatdegree resources and capabilities possessing thesecharacteristics actually improve a firm’s competi-tive position.

In testing these hypotheses, this study seeks toadhere more closely to RBV theory than priorstudies in two important ways. First, given thatresources and capabilities have long been arguedto be effective only when deployed in combi-nation (Penrose, 1959), this study will opera-tionalize the independent variable as the valueand rareness of resource-capability combinationsrather than of individual resources or capabilitiesas is typical of research in this area (Newbert,2007). Second, given that competitive advantageis hypothesized to mediate the resource/capability-performance relationship, this study will avoid thetendency to test the direct effect of resources andcapabilities on performance (Powell, 2001), andinstead explore the intervening effect of competi-tive advantage.

THE RBV

Though the RBV is the result of the efforts of manyscholars (cf. Amit and Schoemaker, 1993; Bar-ney, 1991; Eisenhardt and Martin, 2000; Hender-son and Cockburn, 1994; Penrose, 1959; Peteraf,

1993; Rubin, 1973; Teece et al., 1997; Werner-felt, 1984), Barney is generally acknowledged asthe first to formalize the resource-based literatureinto a comprehensive theoretical framework. In his1991 article, Barney argued that firms that pos-sess and exploit resources and capabilities that arevaluable and rare will attain a competitive advan-tage. Barney further reasoned that these advantageswill ultimately manifest in improved performancein the short term (see Figure 1). Today, the RBV isconsidered to be one of the most widely acceptedtheories of strategic management (Powell, 2001;Priem and Butler, 2001a). However, because therelationships depicted in Figure 1 have receivedonly limited attention in the empirical literature,the RBV’s acceptance appears to be groundedmore on the basis of logic and intuition than onempirical evidence. In light of this condition, thefundamental logic underlying the RBV will be dis-cussed and empirically tested herein.

Value

According to Barney (1991), if a resource or capa-bility yields the potential to enable a firm to reducecosts and/or respond to environmental opportuni-ties and threats, it is valuable, and to the extent thata firm is able to effectively deploy such a resourceor capability, it will attain a competitive advantage.Given this argument, it follows that the magnitudeof a firm’s competitive advantage will be a func-tion of the value of its resources and capabilities.In other words, firms whose resources and capa-bilities are of marginal value will at best attainonly minor competitive advantages. On the otherhand, firms whose resources and capabilities areof great value will likely attain sizable competitiveadvantages. While such logic is straightforward, itnevertheless assumes that the firm is actually capa-ble of exploiting its resources and capabilities; for,only once potentially valuable resources and capa-bilities are effectively deployed can a firm attainwhatever competitive advantages those resources

Resource-capabilitycombination rareness

Resource-capabilitycombination value

Competitiveadvantage

Performance

+

+

+

Figure 1. Conceptual model


748 S. L. Newbert

and capabilities might suggest are available. Inorder to understand how resources and capabili-ties must be exploited, the symbiotic relationshipthat exists among them must be acknowledged.

According to Penrose, ‘resources consist of abundle of potential services . . . [T]he servicesyielded by resources are a function of the way inwhich they are used’ (Penrose, 1959: 25). In orderto effectively use, or exploit, a resource, Amit andSchoemaker argue that a firm must have accessto the appropriate capabilities, which ‘refer to afirm’s capacity to deploy Resources’ (Amit andSchoemaker, 1993: 35, emphasis in original). Inother words, while a given resource may have thepotential to yield a valuable service, that servicewill remain latent until deployed via a relevantcapability.

Clearly, resources and capabilities are inextrica-bly bound together in the attainment of a com-petitive advantage. As Penrose suggests, ‘[no]resources [or capabilities]. . . are of much use bythemselves; any efficient use for them is alwaysviewed in terms of possible combinations withother resources [or capabilities]’ (Penrose, 1959:86). In support, Rubin avers that ‘firms must pro-cess raw resources to make them useful’ (Rubin,1973: 937). Like Penrose (1959), he argues that inorder to effectively process resources, a firm mustuse them in some effective combination. Morerecently, Makadok (2001) contends that firms maycreate rents not only by picking better resourcesthan competing firms, but also by exploiting themmore effectively with the proper capabilities. Hecontinues by suggesting that ‘[n]o matter how greata firm’s capabilities might be, they do not gener-ate economic profit if the firm fails to acquire theresources whose productivity would be enhancedby its capabilities’ (Makadok, 2001: 389).

In summary, it seems that while a resource(or capability) may have tremendous potentialvalue, its value can only be realized when itis combined with a corresponding capability (orresource). Given that resources and capabilities areessentially unproductive in isolation, the key toattaining a competitive advantage is not simply theexploitation of a valuable resource or a valuablecapability, but rather the exploitation of a valu-able resource-capability combination. Moreover,the more valuable the firm’s resource-capabilitycombinations, the greater the advantage it willenjoy as a result of their exploitation.

Hypothesis 1: The value of the resource-capability combinations that a firm exploits willbe positively related to its competitive advan-tage.

Rareness

As noted above, to attain a competitive advan-tage, firms must achieve a cost level, exploit amarket opportunity, and/or neutralize a threat thattheir competitors cannot. Given the novelty asso-ciated with such accomplishments, Barney (1991)reasons that firms are unlikely to achieve theseends if the resources and capabilities they exploitare widely held. Instead, competitive advantagelikely derives from the exploitation of resourcesand capabilities that are rare, or possessed by somenumber of firms in an industry that is small enoughto prohibit perfect competition (Barney, 1991).Along this vein, it is important to note that becauseresources and capabilities must be exploited incombination, to the extent that rareness contributesto competitive advantage, it likely does so not atthe level of individual resources and capabilitiesbut rather at the level of resource-capability com-binations. In support, Barney (1991) acknowledgesthat the criterion of rareness applies to ‘resourcebundles,’ suggesting that if a particular bundle ofresources (and capabilities) is common, then largenumbers of firms will be able to implement theresulting strategy, thereby reducing the advantageto be gleaned from it by each firm.

Given this logic, it seems that firms need notnecessarily possess rare resources and rare capa-bilities in order to attain a competitive advantage.If, for example, a firm possesses a capability thatno other firm does (such as a patented chemicalprocess), it is not necessary for it to possess equallyrare resources in order to translate that capabil-ity’s latent value into a competitive advantage. Tothe extent that this patented process is designed tomanipulate widely available raw materials (such asnaturally occurring chemical compounds), the firmmay still enjoy a competitive advantage over itscompetitors given that its rare capability allows itto exploit common resources differently than otherfirms. Thus, common resources (or capabilities)can be essential to the attainment of a competi-tive advantage provided they are paired with othercapabilities (or resources) in such a way that theresulting combination in which they are exploitedis rare.



In summary, if the resource-capability combina-tions a firm exploits are rare, then it ought to attaina competitive advantage. Moreover, the rarer thesecombinations are, the greater the firm’s advantageswill be.

Hypothesis 2: The rareness of the resource-capability combinations that a firm exploits willbe positively related to its competitive advan-tage.

Competitive advantage

Though the terms competitive advantage and per-formance are often used interchangeably (see Port-er [1985: 11] for example), the two constructs areacknowledged to be conceptually distinct (Pow-ell, 2001). Whereas a competitive advantage isgenerally conceptualized as the implementation ofa strategy not currently being implemented byother firms that facilitates the reduction of costs,the exploitation of market opportunities, and/orthe neutralization of competitive threats (Barney,1991), performance is generally conceptualized asthe rents a firm accrues as a result of the imple-mentation of its strategies (Rumelt, Schendel, andTeece, 1994).

According to Peteraf and Barney (2003), a firmthat has attained a competitive advantage has cre-ated more economic value (the difference betweenthe perceived benefits of a resource-capabilitycombination and the economic cost to exploitthem) than its competitors. The authors continueby suggesting that economic value is generally cre-ated by producing products and/or services witheither greater benefits at the same cost compared tocompetitors (i.e., differentiation-based competitiveadvantage) or the same benefits at lower cost com-pared to competitors (i.e., efficiency-based com-petitive advantage). Because superior benefits tendto enhance customer loyalty and perceived qual-ity (Zou, Fang, and Zhao, 2003), a firm thatcan exploit its resource-capability combinationsto effectively attain a differentiation-based com-petitive advantage should be able to improve itsperformance compared to competitors by sellingmore units at the same margin (i.e., parity price)or by selling the same number of units at a greatermargin (i.e., premium price). Furthermore, becausea superior cost structure enables greater pricingflexibility as well as the ability to increase avail-able surplus (Barua et al., 2004; Porter and Millar,

1985; Zou et al., 2003), a firm that can exploitits resource-capability combinations to effectivelyattain an efficiency-based competitive advantageshould be able to improve its performance com-pared to competitors by selling more units at thesame margin (i.e., low price) or by selling the samenumber of units at a greater margin (i.e., parityprice). In either case, it is logical to assume that afirm that attains a competitive advantage, whetherin the form of greater benefits at the same costor the same benefits at lower cost, will be able toimprove its performance in ways that its competi-tors cannot.

This assumption, however, should not imply thatcompetitive advantage and performance will nec-essarily be equivalent from an empirical standpointfor at least two reasons. First, although a compet-itive advantage may be a sufficient condition forimproved performance, it may often be unneces-sary (Durand, 2002). Indeed, the implementationof a resource-based strategy is simply one of manymeans by which a firm might earn rents. In sup-port, there is a wealth of empirical evidence sug-gesting that many factors exogenous to the firmsignificantly affect performance (Brush, Bromiley,and Hendrickx, 1999; Datta, Guthrie, and Wright,2005; McGahan and Porter, 1997; Rumelt, 1991;Schmalensee, 1985; Spanos and Lioukas, 2001).Thus, a firm’s performance may increase evenin the absence of a well-executed resource-basedstrategy.

Second, even when a firm does effectivelyimplement a resource-based strategy, it may oftenfind itself unable to recover the resulting economicvalue at a cost lower than that required to createit (Coff, 1999; Peteraf and Barney, 2003). Teece(1987) argues that a firm’s ability to appropri-ate economic value is primarily a function of thenature of the technologies upon which the associ-ated products and services are based and the effec-tiveness of the available forms of legal protection.Given these constraints on value appropriation, anyimprovement in performance a firm experiences isunlikely to correlate perfectly with its competitiveadvantage.

In summary, while it is expected that competi-tive advantage and performance will be correlated,the two constructs are clearly theoretically andempirically distinct. Whereas competitive advan-tage refers to the economic value that has beencreated from the exploitation of a firm’s resource-capability combinations, performance refers to the


750 S. L. Newbert

economic value that the firm has captured fromtheir commercialization. Although a firm’s perfor-mance is influenced by a host of exogenous effects,the competitive advantages a firm attains are nodoubt an important antecedent toward this end.Thus, it is expected that the performance of firmsthat are able to attain competitive advantages willbe greater than the performance of those firms thatare not.

Hypothesis 3: A firm’s competitive advantagewill be positively related to its performance.

According to Barney, ‘firms are able to improvetheir performance only when their [resource-based]strategies exploit opportunities or neutralizethreats’ (Barney, 1991: 106). In other words, thebest performing firms will not necessarily be thosethat simply exploit the most valuable and rareresource-capability combinations, but rather thosefirms that exploit their combinations most effec-tively. In support, Castanias and Helfat (2001)argue that rents derive not from random and/ormisguided initiatives, but rather from properlymotivated and well-directed strategic effort. Thus,in order to improve performance, firms (or morespecifically, firm actors) must first identify andimplement resource-based strategies that actuallyresult in the creation of economic value. Unfortu-nately, the ‘human limitations in crafting firm strat-egy’ (Amit and Schoemaker, 1993: 34) are likelyto result in considerable variation in the degree ofskillfulness with which resource-capability com-binations are exploited. For example, Prahaladand Bettis (1986) observe that individuals oftenmake decisions based on the most readily avail-able (rather than the most accurate) information, aheuristic that invariably leads to the selection ofstrategies that have proven effective in the past.The authors contend that such cognitive biasesmanifest in tremendous variance in the effective-ness of decisions regarding resource utilization. Inother words, because decisions tend to be basedon idiosyncratic and often erroneous information,firms may often implement resource-based strate-gies that do not result in improved performance.

It seems then that while some firms will be ableto gain access to potentially valuable resources andcapabilities that other firms will not (Barney, 1986;Dierickx and Cool, 1989), their mere exploitationcannot ensure the appropriation of positive eco-nomic rents. In order to reap any performance

benefits from its valuable, rare resources and capa-bilities, the firm must deploy them in combinationsthat actually result in the reduction of costs, theexploitation of market opportunities, and/or theneutralization of environmental threats. It is pre-cisely because of the fact that a firm may notnecessarily succeed in attaining these ends thatits performance is ultimately a function of theeffectiveness with which it exploits its resource-capability combinations, as opposed to their under-lying value and rareness.

The above discussion is not intended to sug-gest that the value and rareness of the resource-capability combinations a firm exploits play norole in determining its performance. Indeed, inorder to deliver a product or service with uniquefeatures and/or at lower cost than competitors,a firm must exploit valuable resource-capabilitycombinations in ways that its competitors do not.At the same time, however, no matter how valu-able and rare these combinations are, they willnot directly predict a firm’s performance. In orderto earn rents from its resource-capability combi-nations, a firm must successfully attain the com-petitive advantages that result from their exploita-tion. Thus, while a firm may find itself unableto improve its performance in the absence ofvaluable, rare resource-capability combinations, itis the competitive advantages that derive fromtheir exploitation that will ultimately determine thefirm’s level of performance.

Hypothesis 4: A firm’s competitive advantagewill mediate the relationship between the valueof the resource-capability combinations that thefirm exploits and its performance.

Hypothesis 5: A firm’s competitive advantagewill mediate the relationship between the rare-ness of the resource-capability combinationsthat the firm exploits and its performance.

METHODOLOGY

Sample

In their assessment of what has been learned fromthe RBV literature, Barney and Mackey arguethat ‘the best resource-based empirical work willinvolve collecting primary data from firms in acarefully drawn sample’ (Barney and Mackey,



2005: 5). In response to this call, a sample ofmicro- and nanotechnology firms was surveyedfrom the fall of 2003 through the spring of 2004.Micro- and nanotechnology firms were chosen fortwo reasons. First, scholars have argued that com-petitive advantages are exceedingly difficult, if notimpossible, to sustain in dynamic markets (Brownand Eisenhardt, 1998; D’Aveni, 1994; Lei, Hitt,and Bettis, 1996; Teece et al., 1997). In such cases,scholars argue that the best a firm can hope for isto attain ‘a series of temporary advantages’ (Eisen-hardt and Martin, 2000: 1118). Given that thisstudy seeks to understand how firms may attain (asopposed to sustain) competitive advantages, firmscompeting in a dynamic environment that are con-tinuously seeking to do so makes for an appropriatesample.

Second, because of the infancy of micro- andnanotechnologies, they have yet to gain the legit-imacy necessary to stimulate widespread adoptionby potential customers (Aldrich and Fiol, 1994).Due to the absence of a known demand, the attain-ment of a competitive advantage in this sector maynot always translate into improved performance.Therefore, the present sample may offer insightswith regard to the important mediating role com-petitive advantage plays in the resource/capability-performance relationship.

Because a sizable proportion of U.S. firms areprivately held, analyzing a sample of publiclytraded micro- and nanotechnology firms wouldonly produce biased results. In order to identifya more representative sample of firms, the mailinglist for the Micro and Nanotechnology Commer-cialization Education Foundation (MANCEF), atrade organization designed to facilitate the com-mercialization of micro- and nano-based technolo-gies, was obtained. This list consisted of senior-level executives at MANCEF member firms, 30.8percent of which were found to be privately held.Of these names, those with valid mailing addressesworking at firms directly involved in micro- andnanotechnology sectors at for-profit firms wereselected, yielding a usable sample size of 664.These 664 firms were found to compete in a varietyof industries, of which semiconductors, chemicals,electronics, computer equipment, communications,and aerospace were the most commonly repre-sented. Because many of the public firms in thesample were known to be multidivisional, eachrespondent was asked to consider only the division

that competes directly in the micro- and nanotech-nology sector when responding to the survey.

Variables

Competitive advantage, value, and rareness

Given that firms are widely acknowledged tobe bundles of resources and capabilities (Bar-ney, 1991; Penrose, 1959; Rubin, 1973; Wern-erfelt, 1984), it is unlikely that a firm’s com-petitive position is solely attributable to any onespecific resource or capability. Therefore, unlikeprior conceptual-level studies (i.e., Markman et al.,2004), a focus on specific resources or capabili-ties was avoided. Instead, this study focuses onthe value and rareness of as well as the competi-tive advantages attained from the exploitation ofthe firm’s entire resource/capability base. In sodoing, it is hoped that any subsequent findings willbe generalizable to all resources and capabilitiesexploited by all firms in the context.

Because respondents would likely be unable toassess the value and rareness of each individ-ual resource and capability controlled by the firmdue to bounded rationality (Simon, 1957), it wasdecided that the entire resource/capability basemight be best assessed by asking respondents tocomment on several broad categories of resourcesand capabilities. Due to its widespread use, Bar-ney’s (1997) typology (financial, human, organiza-tional, and physical resources and capabilities) wasidentified by a team of two academics as an appro-priate starting point. After consulting with fivesenior-level executives at five different technol-ogy firms, the category ‘intellectual resources andcapabilities’ was added to the typology to makeit more comprehensive and relevant to micro- andnanotechnology firms (see Appendix).

Items were then constructed with careful atten-tion to the fact that each firm competes with aunique set of competitors, maintains an idiosyn-cratic set of strategic objectives, and is subject todifferent environmental contingencies. Therefore,respondents were asked to assess the resources andcapabilities their firms exploited for the purposesof reducing costs to a ‘competitive’ level, exploit-ing ‘targeted’ opportunities, and defending against‘known’ threats. By positioning the items in thisfashion, any a priori assumptions on the part ofthe researcher regarding what ought to constitutean appropriate cost structure, what opportunities


752 S. L. Newbert

ought to be exploited, and what threats ought towarrant a response were avoided (see Appendix).

Competitive advantage. Barney (1991) definescompetitive advantage as the degree to which afirm has reduced costs, exploited opportunities,and neutralized threats. To measure competitiveadvantage, items were initially developed by theacademic team in accord with this operational def-inition as suggested by Kerlinger and Lee (2000:chap. 3). These items were then reviewed by thepractitioner panel in order to ensure their clar-ity and relevance to non-academics. Through aniterative ratification process between the academicteam and practitioner panel, a set of three itemsemerged (see Appendix, items CA1–CA3). Theseitems are positively coded, such that the higher theresponse, the greater the firm’s competitive advan-tage.

In operationalizing this variable, responses tothese three items were summed for each resource/capability category, resulting in five scores thatreflected the competitive advantages the firm hadattained from the exploitation of its financial,human, intellectual, organizational, or physicalresource-capability combinations. For example, thecompetitive advantage attained from a firm’s finan-cial resource-capability combinations was calcu-lated as: CA1a + CA2a + CA3a. Finally, a com-posite score reflecting the average level of com-petitive advantage across all resource/capabilitycategories was created by averaging these fivescores.

Value. Harrison, McLaughlin, and Coalter (1996)note that when the constructs under empiricalexamination are similar conceptually, the poten-tial for highly correlated responses is increased.Because the definitions of value and competitiveadvantage have been argued to be tautological(Priem and Butler, 2001a, 2001b), respondent biasof this nature was a concern. To mitigate this issue,two steps were taken in the construction of thevalue items.

First, a multi-item scale was used given evi-dence that response bias decreases as the numberof items measuring each construct increases (Har-rison et al., 1996). Second, respondents were askedto comment indirectly about the value of theirfirm’s resources and capabilities. Indirect framingwas used to reduce the likelihood that respondentswould seek to rationalize responses describing the

level of competitive advantage their firms hadattained with the value of the underlying resourcesand capabilities. Specifically, items were devel-oped that asked respondents to consider, regard-less of whether or to what degree their firms hadattained a competitive advantage, if access to other(i.e., more valuable) resources or capabilities mightenable their firms to improve any such advantages.By assessing value in this manner, the potentialfor response bias is reduced as prior responsesregarding the firm’s competitive advantage needno justification.

Relying on this logic, six items measuring valueemerged from the iterative ratification process dis-cussed above (see Appendix, items V1–V6). Intheir raw form these items are negatively codedsuch that the higher the response, the more effec-tively the firm could reduce costs, exploit oppor-tunities, and/or neutralize threats with access toresources and capabilities that are currently beyondthe firm’s control. In other words, the higher theresponse, the less valuable those resources andcapabilities that the firm does control. Once thesurveys were returned, responses to these itemswere recoded (i.e., positively coded) such thatthe higher the response, the more valuable theresources and capabilities to which the firm hasaccess.

As argued above, a resource is exponentiallymore valuable when combined with the appropri-ate capability. Therefore, the value of a resource-capability combination ought to be a multiplicative(as opposed to additive) function of the value of theindividual resources and capabilities that compriseit. Given this logic, responses to each of the capa-bility value items (V1, V3, V5) were multiplied bythe corresponding resource value items (V2, V4,V6, respectively), resulting in three preliminaryvalue scores reflecting the firm’s ability to reducecosts to a competitive level, exploit targeted oppor-tunities, and neutralize known threats with theresources and capabilities to which it has access.These preliminary scores were computed for eachresource/capability category and then summed,resulting in five scores reflecting the overall valueof each firm’s financial, human, intellectual, orga-nizational, or physical resource-capability combi-nations. For example, the value of a firm’s finan-cial resource-capability combinations was calcu-lated as: V1a × V2a + V3a × V4a + V5a × V6a.Finally, a composite score reflecting the average



value of all of the firm’s resource-capability com-binations was computed by averaging these fivescores.

Rareness. In order to confer a competitive advan-tage, a given resource-capability combination mustbe exploited by a small number of firms. However,as noted above, common resources and capabili-ties often play an important role in the attainmentof a competitive advantage. Therefore, items mea-suring rareness must account for the degree towhich a firm exploits unique resource-capabilitycombinations as well as the degree to whichit exploits common resources (or capabilities)with unique capabilities (or resources). Followingthis logic, three items measuring rareness weredeveloped conjointly by the academic team andpractitioner panel (see Appendix, items R1–R3).These items are positively coded such that thehigher the response, the rarer the firm’s resource-capability combinations. In operationalizing thisconstruct, responses to these three items weresummed for each resource/capability category,resulting in five scores that reflected the rareness ofeach firm’s financial, human, intellectual, organi-zational, or physical resource-capability combina-tions. For example, the rareness of a firm’s finan-cial resource-capability combinations was calcu-lated as: R1a + R2a + R3a. Finally, a compositescore reflecting the average rareness of all of thefirm’s resource-capability combinations was com-puted by averaging these five scores.

Illustrative example. To illustrate how the abovescales measure the constructs at issue, considera simplified example in which a population oftwo firms produce oil from separate but identicaldeposits of bitumen, or ‘oil sand,’ a highly viscousform of petroleum (a physical resource). Supposethat Firm A possesses high-quality surface miningcapabilities (a conventional technology wherebythe land is strip-mined to extract bitumen at shal-low depths) and steam injection capabilities (aconventional technology whereby steam is pumpedinto the bitumen reservoir to extract bitumen deepunderground). Further suppose that Firm B pos-sesses high-quality surface mining capabilities andfireflood capabilities (an experimental and signifi-cantly more energy efficient technology than steaminjection, whereby the bitumen reservoir is ignitedto extract bitumen deep underground).

Because both firms are producing oil, each hassuccessfully exploited a targeted opportunity and,thus, each has attained a competitive advantage.Yet, because Firm A lacks fireflood capabilities,it has not exploited the opportunity as efficientlyas Firm B, rendering Firm B’s competitive advan-tage greater than Firm A’s. Furthermore, becauseno additional capabilities would enable Firm B tobetter exploit the resource, its capabilities can beconsidered to be extremely valuable. Conversely,because gaining access to fireflood capabilitieswould enable Firm A to exploit the resource moreefficiently, its current set of capabilities can be con-sidered to be less valuable than Firm B’s. Lastly,because each firm combines a common resourcewith one common and one unique capability,the resource-capability combinations exploited byeach firm can be considered to be moderately rare.

Performance

Three types of performance measures are used reg-ularly in the strategy literature: objective financialperformance (Combs and Ketchen, 1999; Knott,2003; Maijoor and Van Witteloostuijn, 1996;Makadok, 1999; Miller and Shamsie, 1996; Robinsand Wiersema, 1995; Russo and Fouts, 1997),subjective financial performance (Powell, 1992a,1992b; 1995; Powell and Dent-Micallef, 1997),and subjective nonfinancial performance (Combsand Ketchen, 1999; Henderson and Cockburn,1994; Markman et al., 2004; Powell and Dent-Micallef, 1997; Yeoh and Roth, 1999). Due tothe prevalence of private firms in the sample,data on objective financial performance were notavailable. Thus, performance was measured viaDelaney and Huselid’s (1996) widely used marketperformance scale (Perry-Smith and Blum, 2000;Richard, 2000), a subjective scale that includesboth financial (sales, profitability) and nonfinan-cial (marketing, market share) indicators and has awell-documented reliability of 0.86 (see Appendix,items P1–P4). These items are positively codedsuch that the higher the response, the greater thefirm’s performance. This variable is operational-ized by summing the responses to the four items.Given that research suggests that perceptual mea-sures of performance correlate well with objectivemeasures (Powell, 1992a), coupled with the ubiq-uity of accounting irregularities in today’s market-place, it is believed that this scale will serve as arigorous indicator of firm performance.


754 S. L. Newbert

Control variables

Authors engaging in RBV research typically con-trol for firm size and the environment. In this study,firm size is operationalized as the firm’s total num-ber of employees. This variable was highly skewedin its raw form; thus, its log was taken in order tonormalize the distribution. In so doing, becauseseveral respondents indicated having no employ-ees, a value of one was added to this item prior totaking its log.

In light of the fact that micro- and nanotech-nology firms do not operate in a single indus-try, and because industry information on manyof the private firms in the sample were unob-tainable, Khandwalla’s (1976) environmental hos-tility scale (see Appendix, items EH1–EH3) isused to control for environmental effects in lieuof Standard Industrial Classification-based mea-sures. This scale is designed to measure the degreeto which the respondent perceives that the firm’senvironment is characterized by competition andrisk and has a well-documented reliability of 0.73.This variable is operationalized by summing theresponses to the three items.

Pilot study

In an attempt to assess the reliability and valid-ity of the newly developed scales (value, rareness,and competitive advantage), a pilot survey wasadministered to 153 of the 664 respondents fol-lowing the Dillman (1978) Total Design Method.1

Surveys and various accompaniments were sentout in a series of three mailings and three e-mails from November 2003 to December 2003,from which 25 completed surveys were received,reflecting a response rate of 16.3 percent. Cron-bach alphas computed on all scales were found tobe above or approaching 0.700, suggesting that thescales are internally consistent (Nunnally, 1978).The results of an exploratory factor analysis ofthese scales show that all items converge withitems measuring the same construct and discrimi-nate from items measuring other constructs. Whilesuch results would ordinarily provide strong evi-dence in support of the scales’ validity, becausethe sample-to-variable ratio of 1.5 : 1 is lower thanthat which is regarded as adequate to derive stable

1 Results pertaining to the reliability and validity of pilot studydata are not reported herein but are available upon request.

factors (Cattell, 1978; Conway and Huffcutt, 2003;Everitt, 1975; Fabrigar et al., 1999), no compellingconclusions regarding validity could be drawn atthis stage.

Full study

Also following the Dillman (1978) Total DesignMethod, the complete survey along with accom-paniments were sent out in a series of four mail-ings and five e-mails from January 2004 to March2004 to the remaining 511 respondents in the sam-ple who were not sent a pilot survey. From these511 respondents, 117 completed surveys werereceived, reflecting a response rate of 22.9 percent,a response rate that compares favorably with simi-lar studies in the field (Alreck and Settle, 1985). Ofthese 117 respondents, 73 provided data regardingtheir job title indicating that 24 (33%) are presi-dent, general manager, partner, and/or chief officer,23 (32%) are senior-level directors or managers, 16(22%) are engineers/scientists, and 10 (14%) arevice presidents. Because those responding to thesurvey are all senior-level executives or scientistsat their respective firms, it is assumed that they areall highly qualified to provide accurate responsesto the survey items.

In order to test for the presence of bias amongrespondents, several tests were conducted.2 First,chi-square tests were conducted to determine ifrespondents differed from nonrespondents basedon their gender or the geographic location of theirfirm. All statistics were insignificant, suggestingthat respondents and nonrespondents do not differon these dimensions.

Second, ANOVA tests were then conducted foreach survey item to determine if the answersgiven by early responders (those whose surveywas received prior to the third mailing, n = 60)differed significantly from late responders (thosewhose survey was received after the third mailing,n = 57). Of the 68 items on the survey, signifi-cant differences existed between these two groupsfor only four (5.88%). Because five percent of themean responses are expected to be significantlydifferent at the p = 0.05 level by chance alone, thefact that significant differences were found to existfor only 5.88 percent of the items is not entirelyunexpected. Thus, it is assumed that any bias that

2 Results of tests of response bias are not reported herein but areavailable upon request.



may exist with respect to the time of response isdue largely to chance and will not substantivelyimpact any subsequent analyses.

Lastly, a Harman’s single-factor test was con-ducted to assess the degree to which the datais subject to common method bias, an approachthat is routinely used in the literature (Christmann,2004; Kirkman and Shapiro, 2001; Steensma et al.,2005). The unrotated factor solution produced fivefactors that account for 23.1 percent, 18.3 percent,11.4 percent, 7.6 percent, and 6.9 percent of thevariance, respectively. Because a single factor didnot emerge from the analysis and because no sin-gle factor accounted for a substantial majority ofthe variance, artificial response bias is not assumedto exist in the data (Podsakoff and Organ, 1986).

In order to assess the reliability of the data,Cronbach alphas were computed for each scaleused in the full study (see Appendix for reliabil-ity coefficients). Alphas for all scales are above orapproaching 0.700, suggesting that the scales are

internally consistent (Nunnally, 1978). In order toassess the validity of these scales, an exploratoryfactor analysis was conducted on the 19 items com-prising these constructs (see Table 1 for results).With a usable sample size of 96, this analy-sis yields a sample-to-variable ratio of 5.1 : 1.Scholars have traditionally relied on anecdotalevidence when proposing appropriate sample-to-variance ratios (MacCallum et al., 1999), resultingin wide-ranging recommendations, from a low of3 : 1 (Cattell, 1978) to a high of 10 : 1 (Everitt,1975). More recently, however, rigorous statisti-cal studies of exploratory factor analysis find thata ratio of 4 : 1 is adequate to produce stable fac-tors (Conway and Huffcutt, 2003; Fabrigar et al.,1999). In light of such evidence, it is concludedthat the factors reported in Table 1 are stable. Fur-thermore, given that the items in Table 1 convergewith items measuring the same construct and dis-criminate from items measuring other constructs(reaffirming the inconclusive pilot study results),

Table 1. Exploratory factor analysis: full study

Value Rareness Competitiveadvantage

Performance Environmentalhostility

Survey Item1,2

Capabilities enable threat response (V5) 0.794 0.025 −0.013 −0.042 0.021Resources enable threat response (V6) 0.777 −0.148 0.180 −0.113 −0.016Capabilities enable opportunity exploitation (V3) 0.767 0.176 −0.277 −0.014 −0.107Resources enable opportunity exploitation (V4) 0.741 −0.197 0.296 −0.011 −0.090Capabilities enable cost reduction (V1) 0.720 0.054 −0.070 0.250 0.124Resources enable cost reduction (V2) 0.649 −0.149 0.122 0.025 0.263Combine resources with novel capabilities (R2) −0.017 0.874 0.066 0.189 −0.097Combine novel resources and capabilities (R3) −0.126 0.845 0.106 0.074 0.077Combine capabilities with novel resources (R1) −0.077 0.783 0.325 0.123 −0.001Threats responded to (CA3) 0.047 0.177 0.835 0.165 −0.113Opportunities capitalized on (CA2) 0.140 0.315 0.759 0.175 0.060Costs highly competitive (CA1) 0.054 0.469 0.424 0.379 0.023Growth in sales (P2) 0.060 0.078 0.120 0.888 −0.188Profitability (P3) 0.029 0.138 0.189 0.807 −0.155Market share (P4) −0.133 0.007 0.354 0.717 −0.096Marketing (P1) 0.051 0.203 −0.089 0.689 0.055Safety of environment (EH2) 0.084 −0.093 0.020 0.037 0.831Richness of opportunities (EH3) −0.033 −0.083 0.009 −0.174 0.725Control over environment (EH1) 0.083 0.304 −0.127 −0.164 0.658StatisticsEigenvalue 4.391 2.168 1.450 3.481 1.307Variance explained 17.878 14.382 10.475 14.849 9.772

1 Note that the statistics reported for the value, rareness and competitive advantage items reflect the factor weights for the averageresource/capability category. Exploratory factor analyses for each of the individual resource/capability categories are similar, thoughthey are not reported herein.2 Item number in parentheses (see Appendix).N = 9667.4% of the variance explained.


756 S. L. Newbert

it is also concluded that the scales used in thisstudy are indeed valid indicators of the constructsthey were developed to measure.

ANALYSIS AND RESULTS

Descriptives and correlations

Descriptive statistics and correlations were com-puted for the model variables (see Table 2). Twosets of statistics are worthy of note in Table 2.First, of the correlations among variables thatwill appear conjointly in subsequent regressionanalyses (bolded statistics), those that are sig-nificant are all below 0.500 with the exceptionof that between rareness (organizational resourcesand capabilities) and competitive advantage (orga-nizational resources and capabilities). However,because the variance inflation factor (VIF) forthese two terms is 1.452, well below the VIF of10 that Kennedy suggests is indicative of ‘harmfulcollinearity’ (Kennedy, 1992: 183), it is assumedthat this correlation will not confound the results ofany subsequent statistical tests.3 Second, the corre-lations among the value and competitive advantageitems are relatively low (the maximum r across thefive resource/capability categories is 0.358). Suchevidence suggests that efforts to mitigate bias inthe form of highly correlated responses for thesetwo constructs were successful.

Determinants of competitive advantage

Hypotheses 1 and 2 were tested using six hierarchi-cal ordinary least squares (OLS) regression mod-els, one pertaining to each of the five individualresource/capability categories (financial, human,intellectual, organizational, and physical, respec-tively) and one pertaining to the average for thesecategories. As can be seen from the results of theseanalyses reported in Table 3, the F -statistics andthe changes in the F -statistics for all six regressionmodels are significant, suggesting not only that thefull models fit the data well, but also that the addi-tion of the independent variables produces modelsthat fit the data significantly better than the con-trol variables models. The results also show thatthe full models explain a considerable amount ofthe variance in competitive advantage (11.9% to

3 The VIF is calculated as 1/(1 − r2).

32.6% across the six models), which in each casereflects a substantial increase from the control vari-able model.

The parameters for the control variables showthat firm size is insignificant in all six modelsand that environmental hostility is significant inthe financial resources and capabilities model only,suggesting that these variables have little or noeffect on competitive advantage. With respect tothe hypotheses at issue, the parameter estimate forvalue is positive and significant in five of the sixmodels (all but the physical resources and capabili-ties model). This finding offers support for Hypoth-esis 1, that the value of the resource-capabilitycombinations that a firm exploits is positivelyrelated to its competitive advantage. Additionally,the parameter estimate for rareness is significantand positive in all six models. This finding sug-gests that the rarer a firm’s resource-capabilitycombinations, the greater the competitive advan-tages it will attain from their exploitation. Thus,support is also concluded for Hypothesis 2.

Determinants of performance

Hypotheses 3, 4, and 5 were tested using six hier-archical OLS regression models similar to thosediscussed above. As can be seen from the resultsof these analyses reported in Table 4, all six F -statistics and five of the six changes in the F -statistics are significant suggesting that the fullmodel not only fits the data well, but also thatthe addition of competitive advantage to the modelsignificantly improves the fit of the data for all butthe physical resources and capabilities model. Theresults also show that the full models explain aconsiderable amount of the explained variance inperformance (11.8% to 18.6% across the six mod-els for which the inclusion of competitive advan-tage improves the model’s fit), which in each casereflects a substantial increase from the control vari-able model.

The parameter estimates for the control variablesshow that environmental hostility is significantlyand negatively related to performance in all sixregression models. This finding, which is consis-tent with prior research (Dess et al., 2003), sug-gests that the less hostile a firm’s environment, thegreater its performance. Firm size, on the otherhand, is insignificant in all models, suggestingthat this variable is unrelated to performance. Theresults also show that the parameter estimate for



Tabl

e2.

Des

crip

tives

and

corr

elat

ions

1

Var

iabl

e2M

ean

Std.

dev.

N1

23

45

67

89

1E

nvir

onm

enta

lho

stili

ty11

.938

3.12

011

22

Firm

size

(log

)4.

911

3.00

410

5−

0.17

73

Val

ue(fi

nanc

ial)

21.8

7212

.500

109

−0.

104

0.29

4∗∗

4V

alue

(hum

an)

22.0

5510

.683

109

0.18

90.

129

0.42

5∗∗∗

5V

alue

(int

elle

ctua

l)22

.798

11.4

8010

90.

117

0.08

60.

314∗∗

∗0.

624∗∗

∗

6V

alue

(org

aniz

atio

nal)

22.5

0011

.245

108

0.15

00.

159

0.38

4∗∗∗

0.66

0∗∗∗

0.72

9∗∗∗

7V

alue

(phy

sica

l)24

.560

11.0

6910

90.

012

0.24

2∗0.

696∗∗

∗0.

667∗∗

∗0.

469∗∗

∗0.

450∗∗

∗

8V

alue

(ave

rage

)22

.347

9.02

610

90.

107

0.21

9∗0.

704∗∗

∗0.

845∗∗

∗0.

797∗∗

∗0.

813∗∗

∗0.

798∗∗

∗

9R

aren

ess

(fina

ncia

l)9.

860

2.22

110

70.

049

−0.

143

0.02

10.

021

−0.1

65−0

.121

0.01

3−0

.051

10R

aren

ess

(hum

an)

10.3

002.

224

107

0.02

0−

0.36

0∗∗∗

−0.3

39∗∗

∗0.

026

−0.0

02−0

.040

−0.1

82−0

.118

0.35

6∗∗∗

11R

aren

ess

(int

elle

ctua

l)10

.590

2.52

510

70.

023

−0.

302∗∗

−0.4

32∗∗

∗−0

.078

−0.

024

−0.0

45−0

.375

∗∗∗

−0.2

16∗

0.35

3∗∗∗

12R

aren

ess

(org

aniz

atio

nal)

9.91

02.

255

107

0.08

2−

0.09

6−0

.119

0.08

90.

043

0.16

4−0

.077

0.04

10.

412∗∗

∗

13R

aren

ess

(phy

sica

l)9.

900

2.17

210

7−

0.05

9−

0.28

7∗∗−0

.099

0.14

5−0

.041

−0.0

240.

041

−0.0

060.

470∗∗

∗

14R

aren

ess

(ave

rage

)10

.110

1.74

810

70.

031

−0.

314∗∗

−0.2

61∗∗

0.04

9−0

.049

−0.0

18−0

.161

−0.

096

0.67

0∗∗∗

15C

ompe

titiv

ead

vant

age

(fina

ncia

l)8.

722

2.53

110

8−

0.15

80.

044

0.35

8∗∗∗

0.03

8−0

.095

0.05

40.

130

0.11

50.

472∗∗

∗

16C

ompe

titiv

ead

vant

age

(hum

an)

9.11

02.

417

109

0.00

7−

0.05

00.

038

0.23

6∗0.

157

0.22

1∗0.

008

0.17

20.

146

17C

ompe

titiv

ead

vant

age

(int

elle

ctua

l)9.

472

2.57

810

80.

006

−0.

243∗

−0.0

980.

024

0.23

4∗0.

189

−0.1

690.

062

0.14

118

Com

petit

ive

adva

ntag

e(o

rgan

izat

iona

l)8.

899

2.33

710

90.

022

0.00

30.

053

0.08

40.

166

0.28

5∗∗−0

.114

0.13

80.

256∗∗

19C

ompe

titiv

ead

vant

age

(phy

sica

l)9.

284

2.23

210

9−

0.05

6−

0.05

50.

165

0.22

6∗0.

114

0.08

60.

235

0.20

1∗0.

292∗∗

20C

ompe

titiv

ead

vant

age

(ave

rage

)9.

099

1.96

610

9−

0.04

2−

0.07

70.

127

0.14

70.

141

0.20

5∗0.

017

0.16

70.

321∗∗

∗

21Pe

rfor

man

ce9.

955

2.97

611

2−

0.24

3∗0.

074

0.08

90.

084

0.05

40.

100

0.02

30.

088

0.14

4


758 S. L. Newbert

Tabl

e2.

(Con

tinu

ed)

Var

iabl

e210

1112

1314

1516

1718

1920

1E

nvir

onm

enta

lho

stil

ity

2Fi

rmsi

ze(l

og)

3V

alue

(fina

ncia

l)4

Val

ue(h

uman

)5

Val

ue(i

ntel

lect

ual)

6V

alue

(org

aniz

atio

nal)

7V

alue

(phy

sica

l)8

Val

ue(a

vera

ge)

9R

aren

ess

(fina

ncia

l)10

Rar

enes

s(h

uman

)11

Rar

enes

s(i

ntel

lect

ual)

0.75

4∗∗∗

12R

aren

ess

(org

aniz

atio

nal)

0.59

6∗∗∗

0.53

8∗∗∗

13R

aren

ess

(phy

sica

l)0.

516∗∗

∗0.

455∗∗

∗0.

374∗∗

∗

14R

aren

ess

(ave

rage

)0.

845∗∗

∗0.

822∗∗

∗0.

763∗∗

∗0.

727∗∗

∗

15C

ompe

titiv

ead

vant

age

(fina

ncia

l)0.

001

0.05

00.

329∗∗

∗0.

212∗∗

0.27

3∗∗

16C

ompe

titiv

ead

vant

age

(hum

an)

0.33

4∗∗∗

0.24

6∗0.

454∗∗

∗0.

336∗∗

∗0.

393∗∗

∗0.

407∗∗

∗

17C

ompe

titiv

ead

vant

age

(int

elle

ctua

l)0.

364∗∗

∗0.

422∗∗

∗0.

385∗∗

∗0.

286∗∗

0.42

0∗∗∗

0.38

5∗∗∗

0.76

5∗∗∗

18C

ompe

titiv

ead

vant

age

(org

aniz

atio

nal)

0.23

7∗0.

271∗∗

0.55

8∗∗∗

0.14

10.

382∗∗

∗0.

554∗∗

∗0.

695∗∗

∗0.

748∗∗

∗

19C

ompe

titiv

ead

vant

age

(phy

sica

l)0.

159

0.13

70.

312∗∗

∗0.

497∗∗

∗0.

358∗∗

∗0.

585∗∗

∗0.

653∗∗

∗0.

516∗∗

∗0.

474∗∗

∗

20C

ompe

titiv

ead

vant

age

(ave

rage

)0.

270∗∗

0.27

9∗∗0.

500∗∗

∗0.

356∗∗

∗0.

448∗∗

∗0.

723∗∗

∗0.

864∗∗

∗0.

842∗∗

∗0.

853∗∗

∗0.

785∗∗

∗

21Pe

rfor

man

ce0.

024

0.05

20.

289∗∗

0.09

60.

156

0.37

3∗∗∗

0.29

9∗∗0.

309∗∗

∗0.

383∗∗

∗0.

258∗∗

0.39

9∗∗∗

∗ p<

0.05

,∗∗

p<

0.01

,∗∗

∗p

<0.

001

1B

olde

dco

effic

ient

sin

dica

teth

ose

corr

elat

ions

amon

gva

riab

les

that

will

appe

arto

geth

erin

subs

eque

ntO

LS

regr

essi

ons

2R

esou

rce/

capa

bilit

yty

pein

pare

nthe

ses

(see

App

endi

x)



Tabl

e3.

Det

erm

inan

tsof

com

petit

ive

adva

ntag

e

Fina

ncia

lre

sour

ces

and

capa

bilit

ies1

Hum

anre

sour

ces

and

capa

bilit

ies2

Inte

llect

ual

reso

urce

san

dca

pabi

litie

s1

Org

aniz

atio

nal

reso

urce

san

dca

pabi

litie

s1

Phys

ical

Res

ourc

esan

dC

apab

ilitie

s2

Ave

rage

Res

ourc

esan

dC

apab

ilitie

s2

Env

iron

men

tal

host

ilit

y−0

.191

−0.1

78∗

−0.0

07−0

.040

−0.0

46−0

.059

−0.0

09−0

.059

−0.1

01−0

.052

−0.0

82−0

.093

Firm

size

0.01

1−0

.016

−0.0

440.

033

−0.2

52∗

−0.1

75+

0.00

00.

008

−0.0

540.

056

−0.0

850.

010

Val

ue0.

311∗∗

∗0.

215∗

0.25

6∗∗0.

194∗

0.14

50.

187+

Rar

enes

s0.

449∗∗

∗0.

332∗∗

0.38

3∗∗∗

0.53

8∗∗∗

0.48

7∗∗∗

0.46

0∗∗∗

Adj

uste

dR

20.

017

0.31

2−0

.019

0.11

90.

041

0.23

1−0

.021

0.32

6−0

.010

0.22

9−0

.009

0.19

5F

-Sta

tistic

1.80

011

.773

∗∗∗

0.08

84.

252∗∗

3.03

6+8.

143∗∗

∗0.

004

12.4

82∗∗

∗0.

533

8.12

0∗∗∗

0.55

06.

813∗∗

∗

FC

hang

e20

.972

∗∗∗

8.40

2∗∗∗

12.5

00∗∗

∗24

.958

∗∗∗

15.5

41∗∗

∗12

.936

∗∗∗

+p

<0.

10,

∗ p<

0.05

,∗∗

p<

0.01

,∗∗

∗p

<0.

001

Stan

dard

ized

coef

ficie

nts

repo

rted

1N

=96

2N

=97

Tabl

e4.

Det

erm

inan

tsof

perf

orm

ance

Fina

ncia

lre

sour

ces

and

capa

bilit

ies1

Hum

anre

sour

ces

and

capa

bilit

ies2

Inte

llect

ual

reso

urce

san

dca

pabi

litie

s1

Org

aniz

atio

nal

reso

urce

san

dca

pabi

litie

s1

Phys

ical

Res

ourc

esan

dC

apab

ilitie

s2

Ave

rage

Res

ourc

esan

dC

apab

ilitie

s2

Env

iron

men

tal

host

ilit

y−0

.240

∗−0

.176

+−0

.252

∗−0

.239

∗−0

.232

∗−0

.206

∗−0

.261

∗∗−0

.238

∗−0

.225

∗−0

.212

∗−0

.239

∗−0

.203

∗

Firm

size

0.07

50.

080

0.06

80.

057

0.08

30.

146

0.05

20.

048

0.09

50.

081

0.10

20.

097

Val

ue−0

.029

−0.1

390.

072

0.00

40.

018

−0.0

790.

046

−0.0

19−0

.077

−0.1

120.

045

−0.0

25R

aren

ess

0.18

0+0.

022

0.11

20.

007

0.11

8−0

.021

0.31

6∗∗0.

147

0.09

8−0

.019

0.22

9∗0.

062

Com

petit

ive

adva

ntag

e0.

354∗∗

0.31

6∗∗0.

365∗∗

0.31

2∗∗0.

240∗

0.36

1∗∗∗

Adj

uste

dR

20.

053

0.13

00.

040

0.11

80.

034

0.12

60.

130

0.18

60.

034

0.06

80.

072

0.16

8F

-Sta

tistic

2.31

1+3.

802∗∗

1.98

53.

543∗∗

1.81

93.

719∗∗

4.52

6∗∗5.

306∗∗

∗1.

845

2.39

7∗2.

842∗

4.82

3∗∗∗

FC

hang

e4.

124∗∗

3.65

3∗3.

988∗∗

6.43

5∗∗∗

1.86

211

.446

∗∗∗

+p

<0.

10,

∗ p<

0.05

,∗∗

p<

0.01

,∗∗

∗p

<0.

001

Stan

dard

ized

coef

ficie

nts

repo

rted

1N

=95

2N

=96


760 S. L. Newbert

competitive advantage is significant and positive inall six regression models, thereby suggesting thata firm’s competitive advantage is indeed an impor-tant antecedent to its performance. Thus, supportis concluded for Hypothesis 3.

It was argued above that the moderately highcorrelation between rareness and competitive ad-vantage would not confound the results for theorganizational resources and capabilities modelpresented in Table 4 given the relatively low VIFfor these constructs. In order to confirm thisassumption, this model was rerun twice, oncewithout rareness and once without competitiveadvantage, in order to assess whether the reportedresults might have been affected by this correla-tion. These additional regressions show that thesignificance, signs, and relative effect sizes of theparameter estimates for the remaining variables arevirtually identical to those presented in Table 4,confirming that this correlation does not confoundthe relationships under examination.4

Mediating effect of competitive advantage

Following Baron and Kenny’s (1986) analyticconsiderations for mediation, the following fourconditions must be met in order to concludesupport for Hypotheses 4 and 5: (1) value andrareness must be related to competitive advan-tage, (2) competitive advantage must be relatedto performance, (3) value and rareness must berelated to performance in the absence of compet-itive advantage, and (4) the effects of value andrareness on performance must be reduced or elim-inated upon the inclusion of competitive advan-tage to the model. The results highlighted aboveshow that the first two of these conditions aremet, namely that value and rareness are relatedto competitive advantage (see Table 3) and thatcompetitive advantage is related to performance(see Table 4). Unfortunately, Baron and Kenny’s(1986) third condition is not satisfied with respectto value. As can be seen in Table 4, the parame-ter estimate for value is insignificant in stage oneof each of the six models. Because no relationshipexists between value and performance, there is norelationship for competitive advantage to mediate;thus, Hypothesis 4 is not supported.

4 Results of these regressions not included herein but are avail-able upon request.

The results for rareness, on the other hand, aremore promising. As seen in Table 4, the param-eter estimates for rareness in the first stage ofthe financial, organizational, and average resourcesand capabilities models are significant, therebysatisfying Baron and Kenny’s (1986) third con-dition. Table 4 also shows that the significanceof each of these parameter estimates is elimi-nated upon the inclusion of competitive advan-tage to the model, thereby satisfying Baron andKenny’s (1986) fourth condition. Taken together,these findings suggest that competitive advan-tage fully mediates the rareness-performance rela-tionship for these three resource/capability cate-gories.

In order to more rigorously assess the mediatingeffect of competitive advantage on the rareness-performance relationship, Sobel, Aroian, andGoodman tests, which are designed to determinewhether the influence that a mediating variable hason the relationship between an independent anddependent variable is statistically significant, wereconducted. As the results in Table 5 show, each ofthese test statistics is significant, suggesting thatthe mediating effect of competitive advantage isindeed significant. Because this effect was foundfor only three of the six models tested, Hypoth-esis 5 is only partial supported. It is important tonote, however, that this mediating effect was foundto exist for the average resources and capabilitiesmodel (suggesting that this effect is significant onaverage), thereby strengthening the partial supportfor this hypothesis.

DISCUSSION

This study was conducted in order to test the RBVhypotheses that the value and rareness of a firm’sresource-capability combinations contribute to itscompetitive advantage and that such an advantage,in turn, contribute to its performance. In findingsupport for Hypotheses 1 and 2—that the morevaluable and rare a firm’s resource-capability com-binations, the more likely it will attain a com-petitive advantage—this is one of only a smallnumber of studies that finds empirical evidence ofdirect relationships between the value and rarenessof a firm’s resource-capability combinations andits competitive advantage. Such findings may beof interest to both academics and practitioners forseveral reasons.



From an academic standpoint, by examiningthese fundamental RBV hypotheses at the con-ceptual level, this study fills an important gapin the empirical literature. The finding that valueand rareness, rather than specific resources andcapabilities, determine a firm’s competitive advan-tage provides support for hypotheses that haveuntil now been accepted almost entirely on thebasis of logic and intuition. Thus, the presentfindings should help strengthen the RBV’s accep-tance as a rigorous theory of strategic manage-ment. Additionally, by framing the independentvariables in terms of resource-capability combina-tions (as opposed to individual resources or capa-bilities), the present study more accurately capturesthe dynamics by which resources and capabilitieshave long been argued to contribute to competitiveadvantage than has the majority of prior researchin this area.

From a practitioner standpoint, the finding thata competitive advantage stems from the combi-nation of valuable, rare resources and capabilitiesmay inform the way in which managers make deci-sions to alter their firms’ resource/capability bases.Consider, for example, that prior research has sug-gested that resources and capabilities may be val-uated in isolation. Such findings imply that if theexploitation of a given resource has not resulted inthe attainment of a competitive advantage, then theresource is not valuable. However, the present find-ings suggest that the resource may indeed be highlyvaluable, but that it must simply be exploited viaa different capability. Thus, before jettisoning oracquiring a given resource (or capability), man-agers may wish to first assess the value of thecapabilities (or resources) with which it has beenor could be combined.

Similarly, prior evidence that only rare resourcesand capabilities will enable the attainment ofa competitive advantage suggests that managers

ought to gain access to resources and capabil-ities that no or few other firms possess. Yet,because rare resources are difficult if not impossi-ble to attain, Miller (2003) theorizes that firms mayinstead be able to build a competitive advantagefrom the resources and capabilities they alreadypossess. The results reported herein support thisargument. Indeed, the finding that it is the unique-ness with which valuable, though perhaps com-mon, resources and capabilities are combined thatenables a firm to attain a competitive advantagesuggests that managers need not necessarily seekout novel resources and capabilities, but ratherdevelop novel ways in which to combine thoseresources and capabilities to which they do haveaccess.

In concluding support for Hypothesis 3, thisstudy finds evidence in support of the notion that acompetitive advantage via the implementation of aresource-based strategy is an important means bywhich a firm can improve its performance. Whenviewed in the context of the results for the media-tion hypotheses (Hypotheses 4 and 5), the currentfindings seem to indicate that although valuable,rare resource-capability combinations are impor-tant in determining a firm’s level of performance,their effect on performance is neither direct norinevitable. Because (1) value and rareness werefound to be significantly related to competitiveadvantage, (2) value was found to be unrelated toperformance, and (3) competitive advantage wasfound to fully mediate the rareness-performancerelationship, it seems that in order to reap any per-formance gains from its resources and capabilities,a firm must first attain the competitive advantagesthat result from their combined exploitation. Inother words, the value and rareness that mightcharacterize a firm’s resources and capabilitiesmay not necessarily confer improved performance.Such an end can only be attained if the firm is able

Table 5. Mediating effect of competitive advantage

Mediated relationship1 Sobel Aroian Goodman

Resource-capability combination rareness (financial) → performance 2.593∗∗ 2.556∗∗ 2.630∗∗

Resource-capability combination rareness (organizational) → performance 2.465∗ 2.439∗ 2.492∗

Resource-capability combination rareness (average) → performance 2.758∗∗ 2.718∗∗ 2.799∗∗

∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.0011 Resource/capability type in parentheses (see Appendix).


762 S. L. Newbert

to exploit these valuable, rare resources and capa-bilities in combinations that enable it to effectivelyreduce costs, exploit market opportunities, and/orneutralize competitive threats. These findings mayalso be informative to both academics and practi-tioners.

From an academic standpoint, these finding areimportant for two reasons. First, by adhering moreclosely to theory, they respond to calls to acknowl-edge the conceptual differences between com-petitive advantage and performance in empiricalresearch (Powell, 2001). Second, by demonstrat-ing that competitive advantage plays a significantrole in the resource/capability exploitation process,they suggest that studies that test the direct rela-tionship between resources/capabilities and perfor-mance may be incomplete.

Taken together with the finding that firm sizeis insignificant in all but one of the 12 regres-sion models, these findings may also be of inter-est to practitioners. To the extent that improv-ing performance is not directly a function of thevalue or rareness of a firm’s resource-capabilitycombinations but rather of the advantages it cre-ates from their exploitation, all firms (both thosethat have access to a wide array of resourcesand capabilities and those that do not) seem tohave an equal opportunity to succeed. Firms seek-ing to improve their performance need not nec-essarily exploit only those resources and capa-bilities that have become the accepted as basesof competition in their respective industry as theresults of resource heterogeneity studies might oth-erwise suggest. Instead, firms need only deploythose resources and capabilities to which theydo have access in novel combinations such thatthey are able to reduce costs and/or respond toenvironmental conditions. Such findings ought togive hope to owners and managers of new andsmall firms as well as those of older firms look-ing to diversify into new markets that may haveaccess to resources and capabilities that are dif-ferent from those to which established competi-tors do.

LIMITATIONS AND DIRECTIONS FORFUTURE RESEARCH

Though the present analysis may provide someinsight into the resource/capability-competitive ad-vantage-performance relationship, it is not entirely

beyond reproach. A concern of any study thatcollects self-report data is that it may be subjectto common method bias. It is important to notethat survey research was undertaken in light ofBarney and Mackey’s (2005) call to conduct pri-mary research on the RBV as well as the fact thatthe context chosen for analysis (the micro- andnanotechnology sector) contains a high percentageof privately held firms for which secondary datais not available. Although the statistical analysesdescribed above suggest that response bias is notpresent in the data, scholars wishing to replicatethis study may nevertheless wish to examine pub-licly held firms for which secondary data may bemore readily obtainable.

Along this vein, it is important to note thatthe data were provided by single respondents.Although the use of single as opposed to multiplerespondents has been argued to increase the like-lihood that the data will be biased, single respon-dents were used for two reasons. First, becausethe MANCEF mailing list was used to identify ageneralizable sample of firms, the list of poten-tial respondents was limited. Second, because therespondents are senior-level executives or scien-tists at their respective firms, they are arguablybetter positioned than anyone else in the firmto assess the firm’s internal operations and com-petitive environment. As such, the data collectedare believed to be accurate. Nevertheless, schol-ars conducting research in this area in the futuremay wish to corroborate their data by surveyingmultiple respondents within the firm.

Lastly, one of the most serious critiques of theRBV, and one to which this study may not beentirely immune, is that of the tautological natureof value and competitive advantage. Given the tau-tology inherent in their operational definitions, anempirical test of the relationship between them isadmittedly difficult. Therefore, multi-item scaleswere diligently created in consultation with prac-titioners with this potential confound in mind inan attempt to avoid unduly correlated responses.Based on evidence that these measures are bothreliable and valid, that respondent bias is notpresent in the data, and that the correlations amongthese two variables are reasonably low, attempts toaccurately measure these constructs were arguablysuccessful.

Nevertheless, because the measurement of value,like that of all unobservable constructs, is inher-ently complicated (Godfrey and Hill, 1995), it



cannot be concluded with certainty that no errorexists in the measurement of this construct. Indeed,the decision to measure value indirectly may haveresulted in data that reflects the subjective shadowprice of a firm’s existing resources and capabil-ities as opposed to their true, objective value.5

To the degree that any such slippage does exist,the results pertaining to value should be acceptedguardedly. Additionally, future scholars may wishto measure value via alternative metrics in anattempt to further reduce the potential confound-ing effects of this tautology while at the sametime capturing the essence of this important con-struct.

Ultimately, this study has endeavored to explorerelationships that underpin many of the fundamen-tal hypotheses of the RBV that have until nowbeen largely ignored in the empirical literature. Infinding support for the majority of these hypothe-ses, this study may help strengthen the RBV’sperception as a rigorous theory of strategic man-agement. Of course, due to the lack of researchin this area, the findings presented herein beckonreplication; thus, future scholars are encouragedto continue to conduct conceptual-level tests ofthe RBV. In so doing, we as a scholarly commu-nity will have more rigorous evidence by whichto confirm, refine, supplement, and/or refute theRBV’s fundamental hypotheses, thereby enrichingour understanding of the role that resources andcapabilities play in an organization’s success andsurvival.

ACKNOWLEDGEMENTS

The author thanks Bruce Kirchhoff, Tom Bryant,Seung Ho Park, Mark Somers, and Shaker Zahrafor their helpful comments on earlier versions ofthis manuscript, and Scott Bryant at the Microand Nanotechnology Commercialization EducationFoundation (MANCEF) for providing the mailinglist used for the data collection. Any remainingerrors are solely the author’s responsibility. Theauthor also acknowledges the Rutgers UniversityPh.D. Program in Management for partially fund-ing this research.

5 The author thanks an anonymous reviewer for raising this issue.

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766 S. L. Newbert

APPENDIX: SURVEY INSTRUCTIONSAND SCALES

Instructions

Below are some questions that will help us learnhow you use your Capabilities and Resourcesfor the purposes of reducing costs to a compet-itive level, exploiting targeted market opportuni-ties, and/or defending against known competitivethreats. When responding to these questions, pleaseselect your answer based on the following defini-tions:

Resources: the tangible or intangible assets a firmpossesses or has access to. Important classes ofResources are as follows:

1. Financial Resources: capital, cash, equity, re-tained earnings, etc.

2. Human Resources: training, experience, judg-ment, intelligence, relationships, etc. of individ-ual employees.

3. Intellectual Resources: patents, copyrights,trademarks, trade secrets, etc.

4. Organizational Resources: relationships withother firms (such as partners, suppliers, buyers,creditors), channels of distribution, corporateculture, etc.

5. Physical Resources: physical technology, plantand equipment, geographic location, raw mate-rials, etc.

Capabilities: the intangible processes (such asskills, abilities, know-how, expertise, designs,management, etc.) with which a firm exploitsResources in the execution of its day-to-day oper-ations.

Performance (Delaney and Huselid, 1996)

Four-point Likert-type scale ranging from muchworse to much better.

Compared to other organizations that do thesame kind of work, how would you compare theorganization’s performance over the past 3 yearsin terms of . . .

P1. Marketing?P2. Growth in sales?P3. Profitability?P4. Market share?

α = 0.821

Competitive advantage

Five-point Likert-type scale ranging from stronglydisagree to strongly agree.

CA1. The manner in which my firm combinesResources and Capabilities enables it toreduce its costs to a highly competitivelevel.

a. Financial Resources and Capabilitiesb. Physical Resources and Capabilitiesc. Human Resources and Capabilitiesd. Intellectual Resources and Capabilitiese. Organizational Resources and Capabilities

CA2. The manner in which my firm combines Re-sources and Capabilities enables it to fullyexploit all targeted market opportunities.


CA3. The manner in which my firm combines Re-sources and Capabilities enables it to defendagainst all known competitive threats.


α = 0.737, 0.691, 0.755, 0.717, and 0.690 forfinancial, human, intellectual, organizational, andphysical resources/capabilities, respectively

Value


V1. Given the Resources my firm possesses andhas access to, if my firm possessed otherCapabilities it could reduce its costs further.

a. Capabilities to exploit Financial Resourcesb. Capabilities to exploit Human Resources



c. Capabilities to exploit Intellectual Resourcesd. Capabilities to exploit Organizational Resourcese. Capabilities to exploit Physical Resources

V2. Given my firm’s Capabilities, if my firm pos-sessed or had access to other Resources itcould reduce its costs further.

a. Financial Resourcesb. Human Resourcesc. Intellectual Resourcesd. Organizational Resourcese. Physical Resources

V3. Given the Resources my firm possesses andhas access to, if my firm had access to otherCapabilities it could better exploit targetedmarket opportunities.

a. Capabilities to exploit Financial Resourcesb. Capabilities to exploit Human Resourcesc. Capabilities to exploit Intellectual Resourcesd. Capabilities to exploit Organizational Resourcese. Capabilities to exploit Physical Resources

V4. Given my firm’s Capabilities, if my firm pos-sessed or had access to other Resources itcould better exploit targeted market opportu-nities.


V5. Given the Resources my firm possesses andhas access to, if my firm had access to otherCapabilities it could better defend againstknown competitive threats.


V6. Given my firm’s Capabilities, if my firm pos-sessed or had access to other Resources itcould better defend against known competi-tive threats.

a. Financial Resources

b. Human Resourcesc. Intellectual Resourcesd. Organizational Resourcese. Physical Resources


Rareness


R1. Compared to companies with similar Capa-bilities, my firm uses them to exploit verydifferent Resources when attempting to reducecosts, exploit market opportunities, and/ordefend against competitive threats.


R2. Compared to companies that possess or haveaccess to similar Resources, my firm exploitsthem with very different Capabilities whenattempting to reduce costs, exploit marketopportunities, and/or defend against competi-tive threats.


R3. Compared to my firm’s competitors, my firmexploits very unique combinations of Re-sources and Capabilities when attempting toreduce costs, exploit market opportunities,and/or defend against competitive threats.




768 S. L. Newbert

Environmental hostility (Khandwalla, 1976)

Seven-point scale reflecting agreement with one oftwo opposing statements about the firm’s environ-ment.

EH1. Very safe, little threat to the survival andwell-being of my firm—Very risky, a falsestep can mean my firm’s undoing.

EH2. Rich in investments and marketing oppor-tunities—Very stressful, exacting, hostile;very hard to keep afloat.

EH3. An environment that my firm can controland manipulate to its own advantage, suchas a dominant firm has in an industry withlittle competition and few hindrances—Adominating environment in which my firm’sinitiatives count for very little against thetremendous competitive, political, or tech-nological forces.

α = 0.622


Documents

Value, Rareness and Competitive Advantage.pdf