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OrganizationScienceVol. 18, No. 2, MarchApril 2007, pp. 181199

issn 1047-7039 eissn 1526-5455 07 1802 0181

informs

doi 10.1287/orsc.1060.0232

2007 INFORMS

Business Model Design and the Performance ofEntrepreneurial Firms

Christoph ZottINSEAD, Boulevard de Constance, 77305 Fontainebleau Cedex, France,

[email protected]

Raphael AmitThe Wharton School, University of Pennsylvania, 3620 Locust Walk,

Philadelphia, Pennsylvania 19104-6370, [email protected]

We focus on the design of an organizations set of boundary-spanning transactionsbusiness model designand askhow business model design affects the performance of entrepreneurial firms. By extending and integrating theoreticalperspectives that inform the study of boundary-spanning organization design, we propose hypotheses about the impact ofefficiency-centered and novelty-centered business model design on the performance of entrepreneurial firms. To test thesehypotheses, we developed and analyzed a unique data set of 190 entrepreneurial firms that were publicly listed on U.S.and European stock exchanges. The empirical results show that novelty-centered business model design matters to theperformance of entrepreneurial firms. Our analysis also shows that this positive relationship is remarkably stable acrosstime, even under varying environmental regimes. Additionally, we find indications of potential diseconomies of scopein design; that is, entrepreneurs attempts to incorporate both efficiency- and novelty-centered design elements into theirbusiness models may be counterproductive.

Key words: organization design; new organizational forms; business model; design themes; organization performance;environmental munificence

Substantial research on organization design has fo-cused on internal design issues such as centralization,span of control, personnel ratios, and lines of authority(e.g., Nystrom and Starbuck 1981). Some scholars, how-ever, have observed that organizations are increasingly

experimenting with their governance of transactions,that is, adopting new ways of structuring their bound-aries (Foss 2002, p. 1). A growing body of work onorganizational forms has gradually shifted attention frominternal design toward modes of organizing and man-aging transactions with the firms environment (e.g.,Ilinitch et al. 1996, Lewin and Volbverda 1999, Milesand Snow 1986, Romanelli 1991). While this body ofresearch has enhanced our understanding of how man-agers and entrepreneurs set organizational boundaries,important questions remain. For example, how can thedesign of an organizations set of boundary-spanningtransactions be described and measured? And what do

we know about the performance implications of differentdesigns?

Recent advances in communication and informationtechnologies, such as the emergence and the swift expan-sion of the Internet, and the rapid decline in com-puting and communication costs, have accentuated thepossibilities for the design of new boundary-spanningorganizational forms (Daft and Lewin 1993, Dunbarand Starbuck 2006, Foss 2002, Ilinitch et al. 1996).Indeed, these developments have opened new horizonsfor the design of business models by enabling firms to

fundamentally change the way they organize and engagein economic exchanges, both within and across firmand industry boundaries (Mendelson 2000). Accordingto Brynjolfsson and Hitt (2004), this includes the waysin which firms interact with suppliers as well as with

customers. An emerging stream of work on boundary-spanning designs complements a large body of literaturethat points to the links between internal organizationdesign issues, such as the degree of decentralization, thestructure of incentives, and the implications on produc-tivity for investment in information technologies (e.g.,see Bresnahan et al. 2002 or Ichniowski et al. 1996).This paper builds on the shift in perspective from view-ing organization form as a complement to IT investmentstoward viewing IT as an enabler of boundary-spanningorganizational design.

In this paper we refer to the design of an organiza-

tions boundary-spanning transactions as business modeldesign, and we ask how business model design can bemeasured, and how it affects firm performance. We for-mally define the business model as depicting the con-tent, structure, and governance of transactions designedso as to create value through the exploitation of busi-ness opportunities (Amit and Zott 2001, p. 511). A busi-ness model elucidates how an organization is linked toexternal stakeholders, and how it engages in economicexchanges with them to create value for all exchangepartners.

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Zott and Amit: Business Model Design and the Performance of Entrepreneurial Firms182 Organization Science 18(2), pp. 181199, 2007 INFORMS

Designing the business model is a salient issue forentrepreneurial firms who are less constrained by pathdependencies and inertia than more established firms(Stinchcombe 1965). Following Bhide (2000), we defineentrepreneurial firms as relatively young organizationsthat have the potential of attaining significant size

and profitability. These firms must solve coordinationproblems in a world of novelty and systemic change(Langlois 2005). Their performance is therefore oftencritically dependent on boundary-spanning organiza-tional arrangements (Hite and Hesterly 2001). One ofthe central design tasks of entrepreneurs is to delin-eate the ways in which their new businesses trans-act with suppliers, customers, and partners. As Irelandet al. (2001, p. 53) note, entrepreneurs often try to findfundamentally new ways of doing business that will dis-rupt an industrys existing competitive rules, leading tothe development of new business models. For example,Christensen (2001) highlighted the shift in the locus of

profitability in the computer industry as companies likeDell pioneered nonintegrated and flexible business mod-els in which production and distribution were organizedin novel ways. Even when entrepreneurial firms replicatethe business models of existing organizations (Aldrich1999), they may have to adapt these designs to their ownparticular market niche (McGrath and MacMillan 2000).

Although recent work in entrepreneurship and organi-zation theory has begun to address the important role ofdesign in the entrepreneurship process (Hargadorn andDouglas 2001, Romme 2003, Van de Ven et al. 1984),relatively little is known about the specific trade-offsand performance implications of business model design,

which can be far-reaching. For example, Hargadorn andDouglas (2001, p. 494) attribute the failure of Prodigy,an online service in which investors had invested $600million, to the mismatch between the design of its busi-ness model and customer needs.

In this paper we identify two critical themes ofbusiness model designefficiency centered and noveltycenteredand offer hypotheses about the impact ofbusiness model design themes on the performance ofthe focal entrepreneurial firm, taking into considera-tion the potentially moderating role of the environment.Efficiency-centered business model design refers to themeasures that firms may take to achieve transaction effi-

ciency through their business models. It aims at reduc-ing transaction costs for all transaction participants.Novelty-centered business model design refers to newways of conducting economic exchanges among vari-ous participants. It can be achieved, for example, byconnecting previously unconnected parties, by linkingtransaction participants in new ways, or by designingnew transaction mechanisms. Efficiency- and novelty-centered designs are neither orthogonal (for instance,novel design elements may engender lower transactioncosts), nor are they mutually exclusive: Both may be

present in any given business model. They are notexhaustive, either. Business models may be characterizedby other value-creation themes. These could includelock-in designs, which attempt to retain stakeholders,and complementarities designs, which emphasize thebundling of goods, activities, resources, or technolo-

gies (Amit and Zott 2001). However, here we focus onefficiency- and novelty-centered designs in the interestof building and testing a parsimonious theory.

To test our hypotheses, we have developed a uniquedata set that contains detailed information about thebusiness models of 190 entrepreneurial firms that werelisted on U.S. or European public exchanges between1996 and 2000. We measure each business model designtheme as a variable at a particular point in time, andwe regress these variables on a range of performancemeasures. Overall, we find that business model designmatters to the performance of entrepreneurial firms.Our most robust finding relates to the positive associ-

ation between novelty-centered business model designand firm performance. Our analysis shows that thispositive relationship is remarkably stable across time,even under varying environmental regimes. Our resultsalso indicate that entrepreneurs attempts to design bothefficiency- and novelty-centered business models may becounterproductive.

This paper builds on and extends earlier work thathas considered business models in the context of or-ganizational performance. Focusing primarily on the im-pact of network effects on the stock market value ofe-commerce firms, Rajgopal et al. (2003) examine how

network effects interact with the firms business model,measured as a categorical variable (i.e., content provider,portal, financial services, e-tailer, or auction site). Inour analysis, we focus primarily on the design of thebusiness model (rather than on network effects), and onits direct impact on firm performance, theoretically aswell as empirically. Our proposed measures of businessmodel design are continuous and apply to a broad rangeof firms. Filson (2004) studies the impact of the com-petitive strategies of Amazon.com, Barnesandnoble.com,CDNow, and N2K on firm value. We, too, focus on firmsthat derive at least some of their revenue through trans-actions that are executed on the Internet. However, we

examine in detail the impact on firm value of businessmodel design, distinct from the competitive strategy ofa firm (Zott and Amit 2006). Our sample size is alsolarge.

Our study attempts to make several contributions tothe organization design literature. First, we refine con-cepts and measures for examining the design of a firmsbusiness model. The importance of research on transac-tion designs as new organizational forms has been rec-ognized in earlier studies, (e.g., Foss 2002, Rindova andKotha 2001). We contribute to this literature through the


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Zott and Amit: Business Model Design and the Performance of Entrepreneurial FirmsOrganization Science 18(2), pp. 181199, 2007 INFORMS 183

development of fine-grained concepts for operational-izing and measuring business model designs. Second,we provide a theoretical extension of the transactioncosts perspective and Schumpeters theory of innovation.By integrating these theories with bargaining theory, wedevelop the performance implications of business model

design, specifically for entrepreneurial firms whosetransactions are enabled by information and communica-tion technologies. To date, little about this has been pub-lished. Third, drawing on a large and a unique data setabout business model design themes, which we have col-lected ourselves, we test the links between these designthemes and focal firm performance. Although we buildon earlier studies that examine how business models arelinked to firm performance (e.g, Rajgopal et al. 2003),we believe that this is the first study to operationalize,measure, and test the performance consequences of busi-ness model design themes. Our study also contributesto the literature on entrepreneurship, by highlighting the

pivotal role that business model design plays in the per-formance of entrepreneurial firms.

To summarize, in this paper we argue theoreticallyand show empirically that the business model is a usefulunit of analysis for research on boundary-spanning orga-nization design, as well as a locus of innovation thathas so far been largely overlooked by entrepreneur-ship research. Rindova and Kotha (2001, p. 1277) havepointed out the need for a broader and more dynamicunderstanding of [organizational] form, in which it isviewed as a flexible arrangement of resources and struc-tures configured to generate a stream of value-creatingproducts and services. The concept of the business

model fulfills these requirements, and can potentiallyhelp advance the emerging body of research on new or-ganizational forms.

The next section presents our theory and hypothesesand is followed by sections describing our data, meth-ods, and our results. We conclude with a discussion ofour findings and the implications of our study for futureresearch.

Theory and Hypotheses Development

Business Model Design Themes

Configuration theory provides a useful starting point for

developing measures of business model design, becauseit considers holistic configurations, or gestalts, of designelements (Miles and Snow 1978). Configurations areconstellations of design elements that commonly occurtogether because their interdependence makes them fallinto patterns (Meyer et al. 1993). The design elementsof a business model are the content, structure, andgovernance of transactions. In this paper, we followMillers (1996) suggestion to view configuration as avariable rather than as a deviation from an ideal type.Miller states that, Configuration can be defined as

the degree to which an organizations elements areorchestrated and connected by a single theme (Miller1996, p. 509).

So what are the common design themes that orches-trate and connect the elements of a business model?Miller (1996) identifies innovation and efficiency. His

choice is particularly appropriate for the study of busi-ness models adopted by entrepreneurial firms becauseinnovation and efficiency reflect fundamental alterna-tives for entrepreneurs to create value under uncertainty.Entrepreneurs can create new designs and/or reproduceand copy existing ones (Aldrich 1999). Imitation-basedapproaches toward business creation are often associ-ated with an emphasis on lower costs, i.e., increasedefficiency (Zott 2003). Because these themes are notmutually exclusive, any given business model design canbe novelty centered and efficiency centered at the sametime.

Business Model Design, Firm Performance, and

the Moderating Role of the EnvironmentWe hypothesize that the design of an entrepreneurialfirms business model, which is centered specifically onthe themes of novelty and/or efficiency, is associatedwith the firms performance. This association can be bro-ken down into two effects: One relies on the total value-creation potential of the business model design, and theother considers the impact of business model design onthe firms ability to appropriate the value that its busi-ness model creates.

Business models can create value either by enhanc-ing the customers willingness to pay or by decreasingsuppliers and partners opportunity costsfor exam-

ple, through improved transaction efficiency. The totalvalue created by a business model is also a function ofthe competitive alternatives, in other words, the marketpower of the focal firms business model vis--vis rivalbusiness models. The total value created is the valuecreated for all business model stakeholders (focal firm,customers, suppliers, and other exchange partners). It isthe upper limit for the value that can be captured by thefocal firm (Brandenburger and Stuart 1996).

How does business model design influence the com-peting claims to total value created by different stakehold-ers in the business model? Drawing on Brandenburger andNalebuff(1995)andBrandenburger and Stuart (1996), wereason that there is a positive association between thedesign of the business model and the performance ofthe focal firmif, for a given level of competition, thefocal firms business model design creates value, and itdoes not decrease its bargaining power relative to otherbusiness model stakeholders.

Environmental conditions seem important as modera-tors of the hypothesized relationship between businessmodel design and the performance of an entrepreneurialfirm (McArthur and Nystrom 1991). Munificence, dy-namism, and complexity are all important dimensions


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higher firm performance when resources are abundantthan when they are scarce.

Hypothesis 2. In environments characterized by high

resource munificence, the positive association between

novelty-centered design and the performance of the

entrepreneurial firm will be stronger than in environ-

ments with low resource munificence.

Efficiency-Centered Business Model

Design and Performance

An alternative way for entrepreneurs to create wealth isto imitate rather than innovateto do things similar toestablished organizations, but in a more efficient way(Aldrich 1999, Zott 2003). To examine the performanceimplications of efficiency-centered business models, webuild on the transaction cost perspective (Milgrom andRoberts 1992; Williamson 1975, 1983), which refersto the design of economic transactions. According to

Williamson (1983), exchange attributes, including infor-mation asymmetry and complexity, determine that trans-actions will be organized into markets or hierarchies inways that minimize transaction costs and maximize per-formance. Researchers generally assume that economicactors whose transactions are unaligned with appropriategovernance structures are more likely to display poorfinancial performance than those whose transactionsare properly aligned (Silverman 2001, p. 484). Poppoand Zenger (1998) have explicitly modeled the perfor-mance implications of the transaction cost perspective,and Milgrom and Roberts (1992) have elaborated on theeffect that transaction costs, in the form of coordina-

tion, and motivation costs have on firm performance.These studies suggest that there is an important directrelationship between the design of transactions and firmperformance.

Efficiency-centered design refers to the measures thatfirms may take to achieve transaction efficiency throughtheir business models. The construct focuses on busi-ness model design and is not intended to capture allmeans by which a firm can strive for efficiency (e.g.,through a reduction of production costs). The essence ofan efficiency-centered business model is the reductionof transaction costs. This reduction can derive from theattenuation of uncertainty, complexity, or information

asymmetry (Williamson 1975), as well as from reducedcoordination costs and transaction risk (Clemons andRow 1992, Langlois 1992, Milgrom and Roberts 1992).The order-tracking feature in Amazons business model,for example, is aimed at enhancing transaction trans-parency and therefore constitutes an efficiency-centereddesign element. It reduces the cost of providing infor-mation to the logistics company, and induces more cus-tomers to check on their packages (Brynjolfsson andHitt 2004). Other efficiency-centered design elementsare intended to increase the reliability and simplicity

of transactions, reduce the asymmetry of informationamong transaction participants, speed up transactions,enable demand aggregation, reduce inventory, providefor transaction scalability, or reduce the direct and in-direct costs of transactions. Consider Baxter ASAP,which lets hospitals order supplies electronically direct

from wholesalers. By reallocating its saved resources(the costs of data entry), the company was able tooffer additional value-adding services to its customers(Brynjolfsson and Hitt 2004). Consequently, we expect apositive primary effect on firm performance of adoptingan efficiency-centered business model design.

As with the novelty-centered business model design,to predict the overall effect of an efficiency-centereddesign on firm performance, we must consider its effecton the firms ability to appropriate the value that it gen-erates. Efficiency-centered business model design aimsat reducing transaction costs, for example, through sim-plified transactions, reduced transaction complexity, or

deep linkages among business model stakeholders thatoften do not require transaction-specific investments(web services, for example). These characteristics ofefficiency-centered business model design are likely toaffect the switching costs for all business model stake-holders in the same direction so that, in the aggregate,the balance of power among these parties will not shift.Importantly, the focal firms bargaining power is unlikelyto decrease.

Another central aspect of efficiency-centered designis that it enables better information flow among stake-holders and reduces information asymmetries amongthe parties, limiting the control over information thatany stakeholder can have. In general, this aspect doesnot negatively affect the focal firms bargaining power.Moreover, the third determinant of the focal firms bar-gaining power identified by Coff (1999, see above)the ability of other business model stakeholders to takeunified action against the focal firmis unlikely to besystematically affected in one direction or the other bydesign efficiency. Last, it should be noted that reducingdirect transaction costs (e.g., search, transportation, andcoordination costs) increases the pool of potential cus-tomers, as well as partners and suppliers, and implies areduction in the cost to the focal firm of replacing such

stakeholders, increasing the firms bargaining power.These arguments suggest that, on balance, a more pro-nounced efficiency-centered business model design doesnot decrease the focal firms bargaining power relative toother business model stakeholders. We therefore expecta positive main effect of efficiency-centered businessmodel design on the performance of an entrepreneurialfirm.

Hypothesis 3. The more efficiency centered an entre-

preneurial firms business model design, the higher the

firms performance.


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When resources are scarce, efficiency-centered busi-ness model design assumes greater importance as a dif-ferentiatingfactorthanin periods of resource munificence.In tough economic environments, consumers and busi-nesses spend and invest less, and cost savings be-come more important as a driver of value creation.

Entrepreneurial firms are more volatile than establishedorganizations (Stinchcombe 1965), so are sensitive tosuch changes. Conversely, during times of high envi-ronmental munificence, total value can be enhanced, forexample, by tapping additional revenue streams. In otherwords, in environments characterized by low resourcemunificence, the advantages derived from reduced trans-action costs are accentuated, while our arguments aboutthe bargaining power of firms with efficient businessmodels continue to hold. Thus, efficient business modeldesign will be more distinctly associated with higherperformance of an entrepreneurial firm when resourcesare scarce than when they are abundant.

Hypothesis 4. In environments characterized by lowresource munificence, the positive association between

efficiency-centered design and the performance of the

entrepreneurial firm will be stronger than in environ-

ments with high resource munificence.

Interaction Between Novelty- and

Efficiency-Centered Business Model Design

and Performance

Do these arguments imply that entrepreneurs shouldembrace both efficiency-centered and novelty-centeredbusiness model designs? The need to balance designelements has been recognized by researchers who high-

light the benefits to entrepreneurs of reconciling distinctaspects of design, such as the familiar and the unfamiliar(Hargadorn and Douglas 2001), conformity and differ-entiation (Deephouse 1999), and reliability and distinc-tiveness (Lounsbury and Glynn 2001). Achieving thisbalance can help entrepreneurs build much-needed legit-imacy (Zott and Huy 2006), a prerequisite for venturegrowth and performance (Zimmerman and Zeitz 2002).This suggests that novelty and efficiency can be com-plementary, and that their interaction could have a pos-itive effect on performance. First, increasing the degreeof novelty of a business model may enhance the returnon efficiency-centered design. Novelty-centered businessmodel design makes a business model more distinctive,and this may result in increased switching costs for otherbusiness model stakeholders because of fewer compara-ble alternatives. By emphasizing business model novelty,the focal firm may be better positioned to appropriatesome of the value it creates through increased efficiency.Second, increasing the emphasis on efficiency-centereddesign may enhance the return on design novelty. Novelbusiness models that are also designed for efficiencymay appeal to a wider range of customers (i.e., not onlyto those who are intrigued by its novel elements, but

also to those who appreciate lower transaction and coor-dination costs). Thus, by simultaneously emphasizingefficiency and novelty as design themes, the entrepreneurmay be able to create even more value than througheither novelty-centered or efficiency-centered businessmodel design alone.

Hypothesis 5. The more novelty centered and effi-ciency centered the business model design, the higher

the performance of the entrepreneurial firm.

However, another line of reasoning suggests that at-tempts by entrepreneurs to design their business modelsfor both higher efficiency and greater novelty may insteadadversely affect their firms performance. Embracing twomajor design themes concurrently could lead to subop-timal resource allocation. Given the limited resourcesavailable to entrepreneurial firms, entrepreneurs who tryto achieve too much at once may find that they are notobtaining adequate returns on their design efforts and

investments. This is because a lack of focus may con-fuse market participants, undermine the ventures legiti-macy, create technological and organizational problems,and lead to higher costs. Furthermore, a firm that getsstuck between innovation and imitationor, analogously,between novelty and efficiency design themesmay per-form poorly because it misses out on the opportunity tolearn to become an even more skillful innovator or imita-tor (Zott 2003). In summary, there might be diseconomiesof scope in design resulting from bundling novel and effi-cient design elements.

Hypothesis 6. The more novelty centered and effi-

ciency centered the business model design, the lower the

performance of the entrepreneurial firm.

Data and Methods

SampleTo test our hypotheses, we studied the business mod-els of firms that derived all or part of their revenuesfrom transactions conducted over the Internet, as thesefirms are likely to experiment with, and take advantageof, the possibilities that advanced information and com-munication technologies offer for the design of busi-ness models. We examined the business models of firmsthat went public in Europe or the United States betweenApril 1996 and May 2000. Our sample selection strat-egy enabled us to create a data set of 362 relativelyyoung entrepreneurial firms and their business models,from which we randomly sampled 201. Limited dataavailability forced us to drop 11 firms from the sample,which left us with a final sample size of 190. We consid-ered public companies, both to ensure the availability ofdata and because data collection from initial public offer-ing documents is an acknowledged method for study-ing entrepreneurial firms (e.g., Dowling and McGee1994). Concerns about survival bias are mitigated by the


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fact that during the sampling period, the threshold forbecoming a public company was relatively low, whichresulted in listing very young and immature companies.As a result, many of the firms in our sample still facedhighly uncertain prospects at the time they went public(Lieberman 2005). Indeed, when we investigated the fate

of these firms in June 2004, we found that 107 of our190 sample firms (56%) had been delisted: 20 had gonebankrupt, 68 had been acquired, 8 had been merged, and11 had been taken private.1

Data CollectionFor each business model design theme, we built com-posite scales and identified and measured relevant itemsin a survey instrument (see Appendix A). The survey-ing process proceeded in five stages: (1) development ofthe survey instrument, (2) development of measurementscales, (3) pretesting of the survey, (4) development ofan online Web interface and of a central database, and(5) data collection.

Following the increasing use of panelists in manage-ment research (e.g., Iansiti and Clark 1994, Lee et al.2003, MacCormack et al. 2001), we hired 11 part- orfull-time research assistants (primarily MBA students),and trained them as raters to fill in the survey instrumentfor assigned sample companies. We carefully selectedour raters from a larger pool of applicants by inter-viewing them and asking them to submit an abbreviatedtest survey on a randomly chosen sample company todisplay their understanding of Internet-based businessmodels. After choosing the most qualified candidates,we trained them in data collection and data analysis.In addition, raters were provided with written guide-lines on the proper way to address survey items. Eachrater was assigned to one of two project managers, whoreviewed completed surveys for internal consistency andcompleteness, but not for the accuracy of each indi-vidual measurement. On average, it took a rater abouttwo and a half days to collect data on a given busi-ness model, to analyze the model, and to complete thesurvey. Data sources included IPO prospectuses, annualreports, investment analysts reports, and websites. Thedata were collected from May 2000 to June 2001. Dur-ing that time period, we took one measurement of thedesign themes for each of the 190 business models inour sample, collecting cross-sectional data on our inde-pendent variables.

We validated interrater reliability by assigning a ran-domly chosen business model to two different raters(each of whom was assigned to a different projectmanager), and by conducting a pairwise comparison ofresponses, yielding a Cronbach alpha of 0.81 and aPearson correlation coefficient of 0.72. Raters were inbroad agreement with each other for 82% of the individ-ual items. We repeated the test periodically for differentraters and different business models and found that allindicators of reliability had further improved.

Independent Variables

We selected two independent variables of businessmodel design: design efficiency and design novelty. Weused 13 items as measures of design efficiency, and 13items as measures of design novelty. Given the diffi-culty of obtaining objective measures of business model

design, we deemed the use of perceptual measuresobtained from our raters appropriate (Dess and Robinson1984). The strength of each of these items in a givenbusiness model was measured using Likert-type scales(see Appendix A for details) and coded into a standard-ized score. After coding, we aggregated the item scoresfor each design theme into an overall score for the com-posite scale using equal weights (see Mendelson 2000).This process yielded distinct quantitative measures ofthe extent to which each business model in the sampleleveraged efficiency and novelty as design themes. (SeeTable 2 for summary statistics.)

We validated the internal consistency and reliability of

our measures using standardized Cronbach alpha coeffi-cients, 0.69 for the design efficiency measure and 0.72for the design novelty measure. Our measures suffi-ciently satisfy Nunnallys (1978) guidelines, which sug-gest 0.7 as a benchmark for internal consistency. Todemonstrate the convergent and discriminate validity ofour measures, we ran a confirmatory factor analysis(CFA). We also employed a partial least squares (PLS)approach to further strengthen our claim about discrim-inant validity. The methods and the results are detailedin Appendix B. Both empirical tests provide support forconstruct validity of our measures.

Dependent VariablesA firms stock market value reflects the markets expec-tations of future cash flows to shareholders, and can beviewed as a measure ofperceivedventure performance.This differs from realizedperformance, which is typi-cally embodied in historical measures of firm profitabil-ity (e.g., ROI, ROA). Given the level of uncertainty oftenassociated with the true prospects of entrepreneurialfirms, perceived performance as stock market value isa particularly suitable measure for an entrepreneurshipsetting (Stuart et al. 1999). Measures of realized perfor-mance such as ROI, ROA, or Tobins qare less appro-priate for young, high-growth entrepreneurial firms that

often have negative earnings, few tangible assets, andlow (even negative) book values. For instance, 134 firmsin our sample (i.e., 86% of the sample firms for whichwe had the relevant accounting data) had negative earn-ings in the fourth quarter (Q4) of 1999. Five firms (i.e.,3% of the sample firms for which we had the relevantdata) even had a negative book value in the same period.These numbers did not change substantially in Q4 2000.

There are limitations in using stock market valuationas a dependent variable. The nature of our sample andthe period in which we collected the data could prompt


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concerns about bias, due to an irrational bubble in thestock market. However, while the rationality of the mar-kets during 19992000 remains an open question (e.g.,Pastor and Veronesi 2004 offer a rational explanationfor investors behavior and provide empirical evidenceagainst the bubble hypothesis), our paper is not pred-

icated on the efficiency of capital markets. It centerson the differential performance implications of alterna-tive business model designs, and our estimation methodexploits their differential valuation by capital markets.Even if the companies in our sample were systematicallyovervalued, this would not distort the qualitative resultsof our regression analysis. An additional support to ourmethodology is the fact that our dependent variable cap-tures market participants perceptions of the businesscycle, and the level of resource munificence in the envi-ronment. It reflects the factors that market participantsvalue (akin to Shleifer and Vishnys 1991 analysis ofstock market valuations of conglomerates in the 1960s

and 1980s). This was actually beneficial for our analysisbecause it allowed us to test our contingency hypothesesabout the moderating effect of resource munificence onthe relationship between business model design and firmperformance.

Because most firms in our sample have relatively lowlevels of debt, the market value of a firms equity is agood approximation of the market value of the wholefirm. We measured the market value of equity at a givendate as the number of shares outstanding multiplied bythe firms stock price, taken from the combined CRSPand Datastream databases. We then calculated the log-arithm of the market value of the equity in order to

comply with the normality assumption of ordinary leastsquares (OLS) regression. Following this transformation,we found that the null hypothesis of normality couldnot be rejected at the 5% level of significance using aShapiro-Wilk test. To test our hypotheses, we used mea-surements of the dependent variable at various pointsin time (annual average, average during Q4, and thelast day of trading of Q4) and in various time peri-ods (1999, 2000) characterized by different levels ofresource munificence for entrepreneurial firms.

Until now, most empirical research has employedindustry-type measures of munificence, such as meanannual industry sales growth (Tushman and Anderson

1986), employment growth in the industry (Dess andBeard 1984), and other indicators of growth at the indus-try level (McArthur and Nystrom 1991). Because thebusiness model construct spans industry boundaries, andmany of the sample firms span multiple industries, wecould not define an industry-level variable that capturedresource munificence adequately. We therefore measuredthe dependent variables in time periods that were suf-ficiently distinct in terms of environmental resourcemunificence, yet close to the point in time when theindependent variables were measured.

Despite the short window, the change in the resourceavailability for entrepreneurial firms triggered by theworldwide crash of high-tech stocks in March 2000 wassevere. Park and Mezias (2005), for example, demon-strate the sharp and statistically significant reversal in anumber of munificence measures. Table 1 summarizes

the differences between the time periods we considered.The year 1999 (and Q4 1999 in particular) was a timeof relatively high munificence for entrepreneurial firmsin our sample, whereas the year 2000 (and Q4 2000 inparticular) was a time of relatively low munificence. Inaddition, other indicators of environmental uncertainty,such as complexity and dynamism (Dess and Beard1984), may have changed between the years, perhaps toa lesser extent.

The use of multiple measures of the dependent vari-able provided a robustness check for our results. In ouranalysis, we contrast the average market value of firmsin Q4 1999 with that in Q4 2000, the market value of

firms at the close of Q4 1999 with that at the close ofQ4 2000, and the average market value of firms in 1999with that in 2000.

Control Variables

We included further factors that might influence themarket value of a firms equity as control variables inthe analysis, because their omission might confoundit. Our industry controls were the level of competi-tive threat, and estimated market size. Our raters mea-sured competitive threat on a four-point Likert scalebased on information found in annual reports, prospec-

tuses, competitors SEC documents and websites, For-rester benchmark studies, Hoovers database (which listseach focal firms main competitors), and investmentanalysts reports. The information on market size wasobtained from Forrester research reports and from theU.S. Department of Commerce. Consistent with marketpower arguments (Porter 1980), and our own theory, thegreater the level of competition that a business modelis facing (in more competitive or smaller markets), thelower the chances that the business model will createmuch total value and the lower the performance of thefocal firm.

Our firm-level controls included the age of the firm,

size, country of origin, and expenditures on R&D, adver-tising, and capital. Size was measured as a logarithm ofthe number of employees. The variable can be viewedas a proxy for the focal firms bargaining power, rela-tive to rival firms and other business model stakehold-ers. All other things being equal, the larger the focalfirm, the greater its potential for value creation as wellas its bargaining power, and, hence, the better its per-formance. We controlled for country of origin using adummy (1 for firms headquartered in North America,0 for European firms).


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Table 1 Indicators of Resource Munificence 1999 and 2000

Indicators of resource munificence

1999 2000

Median quarterly sales growth of sample Median sales growth of sample companies:

companies: 30% (Q2 1999), 29% (Q3 1999), 18% (Q1 2000), 15% (Q2 2000), 8% (Q3 2000),

33% (Q4 1999) 6% (Q4 2000) Number of Internet-related IPOs in United States: Number of Internet-related IPOs in United States:

193 (Q4: 62) 122 (Q4: 0) (2)

Public market Internet IPO financings in % of total Public market Internet IPO financings in % of total

IPO financings: 67% IPO financings: 36% (2)

VC funding for B2C e-commerce companies: VC funding for e-commerce companies dropped

$4.5 billion (+1000% from 1998) (1) from $843 million (Q1) to $69 million (Q4) (3)

Sources. (1) PriceWaterhouseCoopers, http://www.ecommercetimes.com/perl/story/2505.html. (2) Morgan Stanley.

2002. The Technology IPO Yearbook, 8th ed. 22 Years of Tech Investing. http://www.morganstanley.com/institutional/

techresearch/tech_ipo_yearbook.html?page=research. (3) PricewaterhouseCoopers/VentureOne, Money Tree Survey

Q4 2000.

The inclusion of these firm-level variables strength-ens the claim that our analysis captures the influence

of distinct business model design characteristics on firmperformance, as opposed to the effects of firm character-istics or strategy. For example, investment in R&D hasbeen used in prior research as a proxy for technologystrategy (Dowling and McGee 1994) and as a proxy forthe degree to which a firm pursues a product differen-tiation strategy (Mizik and Jacobson 2003). Advertisingexpenditures have been employed as a proxy for a firmsmarketing strategy (Mizik and Jacobson 2003).

Finally, we considered alternative business model de-sign themes, such as complementarities and lock-in(Amit and Zott 2001), by constructing two latent con-trol variables, using 9 indicators for complementarities

(Cronbach alpha = 070), and 15 indicators for lock-in(Cronbach alpha= 074).

Econometric Modeling and Estimation Approach

We analyzed the data using multivariate regression tech-niques. We tested the robustness and validity of ourmodel specification in several distinct ways. First, wetested for multicollinearity among independent variablesby calculating variance inflation factors (VIF) (seeKleinbaum et al. 1998). Second, we performed analysesusing different dependent variables. Third, we discardedinfluential observations based on established criteria foridentifying influential points (e.g., leverage, studentizedresidual, or change in the determinant of the covari-ance matrix) from our data set to see whether they dis-torted results. Fourth, we tested for overfitting of thedata.2 Fifth, we considered the potential bias introducedby sampling on the dependent variable by running atruncated regression model (Maddala 1986).3 Sixth, wetested for homoscedasticity using Whites test. Seventh,we tested for potential endogeneity (i.e., the concernthat business model design could be a choice variablethat is correlated with unobservables that are relegatedto the error term) by running a 2SLS regression with

instrumental variables and by using the Hausmann test(see Greene 2003, p. 80ff).4 Eighth, we performed mul-

tiple partial F-tests (Cohen and Cohen 1983) to ensurethat adding the design novelty and design efficiency vari-ables, as well as their interaction, improved the fit of themodel significantly, compared to a baseline model thatcontained only control variables.

None of these tests gave rise to concern, yet we ob-served multicollinearity in those regressions where theinteraction term between design novelty and design effi-ciency was included. We therefore mean-centered theinteraction variable, as well as the design novelty anddesign efficiency measures (see Aiken and West 1991).This significantly reduced the VIF to levels that atten-uated the concern about multicollinearity. In addition,

we ensured that the mean-centering approach did notentail a lack of invariance of regression coefficients,which may arise in equations containing interactionseven under simple linear transformations of the data(Aiken and West 1991). Overall, therefore, we concludethat our model specification proved robust and valid.

Results

Descriptive Statistics

Table 2a, provides an overview of the data set we assem-bled. It reveals the entrepreneurial nature of our samplefirms as well as the enormous change that occurred inthe environment between Q4 1999 and Q4 2000. Specif-ically, in 1999 the median age of a sample companywas just over four years, while the mean company was

just under seven years old. The few older firms in thesample are those that went through an extensive trans-formation, with entrepreneurial management leading thechange. The median sales of sample companies in 1999were just under $25 million, while the median bookvalue of equity in the same year was $57 million. Themedian sample company employed 269 people (mean1,067). With respect to the change in the environment


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between 1999 and 2000, we note that the median com-pany was worth $349 million at the end of December1999, but only $49 million at the end of December 2000,representing a decline of 85.6% in market value over a12-month period.

Table 2b, depicts the Pearson correlations among the

right-hand side variables used in the regression analy-sis. We note that while some correlations among theexplanatory variables are significant, they do not posea multicollinearity problem, as their variance inflationfactors (VIF) are low.

Hypotheses Tested

Table 3 depicts the OLS regression results. Tables 3aand 3b (full sample) show the results for regressions inwhich the dependent variable is the logarithm of mar-ket value averaged over Q4 1999 (Table 3a), and Q42000 (Table 3b). Table 3c summarizes the main regres-sion results for each of the three dependent variables

we considered. Table 3d (restricted sample) depicts theresults of the same regressions reported in Tables 3a and3b on a restricted sample of firms that were present inboth 1999 and 2000. In other words, in the regressionsreported in Table 3d we control for entry and exit in oursample between 1999 and 2000.

Hypothesis 1 (regarding novelty-centered businessmodel design) is supported by the analysis. As depictedby Table 3 (Tables 3a3d), the coefficient on the designnovelty variable is positive, and in most cases it is signif-icant both during a period of environmental munificenceand during a period of resource scarcity. The observedeffect was relatively robust to changes in the environ-ment. Our results suggest that even in times of resource

Table 2a Descriptive Statistics

Standard

Variable name (acronym) Mean Median deviation Min Max No. observations

Market value at close of Q4 1999 $1,506 $349 $3,184 $2 $25,942 159

US$ million (MVQtr4Close_99)

Market value at close of Q4 2000 $387 $49 $1,101 $07 $8,885 173

US$ million (MVQtr4Close_00)

Design efficiency 0702 0712 0112 0404 092 190

Design novelty 0366 0359 0133 0077 0795 190

Complementarity 0617 0639 0174 0000 0972 190

Lock-in 0454 0463 0140 0167 0763 190Age of firm 70 43 78 04 458 190

Ln number of employees 5723 5593 1336 2833 10342 190

Country (1=United States, 0= European countr y) 088 100 032 000 100 190

R&D expense US$ 00 (million) $27 $05 $64 $00 $67.3 190

Advertising expense US$ 00 (million) $47 $10 $93 $00 $52.8 190

Capital expense US$ 00 (million) $427 $37 $4159 $00 $5,733.1 190

Book value of equity 99 (million) $1637 $573 $4166 $686 $4,601.2 188

Book value of equity 00 (million) $2728 $712 $6852 $9673 $5,752.2 160

Sales net US$ 99 (million) $2633 $249 $1,575.4 $00 $20,111.8 177

Sales net US$ 00 (million) $331.7 $529 $1,643.0 $00 $20,609 177

Number of employees 1,067 269 3,557 17 31,000 190

Market size US$ 00 (million) $20,477 $5,400 $65,640 $120 $744,000 190

scarcity and less uncertainty about the viability of busi-ness model designs, innovative business model designswere associated with higher levels of performance.

Comparing Tables 3a and 3b (full sample) with Table3d (restricted sample), we note that the coefficient on thedesign novelty variable is significant at the 1% level in

the restricted sample for all four models (see Table 3d),while it is significant at the 10% level in the full sam-ple for three of the four models we ran (see Tables 3aand 3b). This might suggest a weakening of the noveltyeffect due to entry dynamics. We explored these appar-ent differences by running a separate set of regressionsusing only the 30 firms that entered our sample in 2000.(These regressions are available from the authors uponrequest.) We observed that in most models the coeffi-cients for novelty-centered business model design werenot significant for this small set of 30 firms. That is,the novelty-centered business model design of the firmsthat entered our sample in 2000 did not significantly

explain the variance in the dependent variable. Further-more, according to the t-test suggested by Cohen andCohen (1983, p. 111), the coefficient on design noveltyin the sample of the 30 entering firms was significantlydifferent from the respective coefficient in the sample in1999.

This analysis highlights the potential role of entry dy-namics for the hypothesized contingent effect of munifi-cence on the relationship between business model designand firm performance. Specifically, under conditions oflow resource munificence, capital markets may be lessreceptive to new public offerings from firms that center

their value proposition on novel business models. Over-all, however, Hypothesis 2 (about the changing strength


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Table 2b Pearson Correlation

Center

eddesign

efficien

cy

Center

eddesign

novelty

Center

eddesign

efficien

cyandcentered

design

novelty

Complementarities

Lock-in

Compe

tition

Log(marketsize)

Age

Log(em

ployees)

Countr

y

R&Dex.00

Adv.ex.00

Capitalex.00

Variable name

(acronym)

Independent variables

Centered design 1000

efficiency

Centered design 0175 1000

novelty

Interaction between 0057 0041 1000

centered design

efficiency and

centered design

novelty

Control variables

Complementarity 0349

0349

0001 1000Lock-in 0316 0413 0173 0373 1000

Competition 0006 0322 0147 0128 0121 1000

Ln market size 0039 0016 0022 0112 0062 0097 1000

Age of firm 0112 0131 0118 0026 0152 0048 0214 1000

Ln number of 0004 0038 0027 0040 0028 0076 0338 0452 1000

employees

Country 0074 0168 0123 0107 0159 0097 0462 0107 0110 1000

R&D expense 00 0066 0220 0049 0088 0140 0011 0022 0027 0281 0123 1000

Advertising 0088 0020 0037 0042 0002 0027 0199 0223 0493 0178 0434 1000

expense 00

Capital expense 00 0004 0018 0004 0147 0075 0055 0066 0355 0271 0036 0001 0414 1.000

001 p < 005, p < 001, 005 p < 01.

of the design novelty coefficient in different environ-ments) receives little support from our data. FollowingGatignon (2003), we examined the moderating role ofenvironmental munificence by conducting a Chow testfor the equality of the coefficients in the overall modelbetween the 1999 and 2000 regressions. The test pro-vided significant results (see Table 4). This led us tofurther examine whether the coefficient on design nov-elty caused the observed structural break suggested byTable 3c. The table shows that the regression coeffi-cients on the design novelty variable were highly signif-icant in 1999, but less so in 2000. To confirm whetherthis effect was statistically significant, we conducted a

series of pooled regression runs (for all models and alldependent variables): (a) on a completely unrestrictedmodel, in which we included a year dummy (zero for1999, one for 2000) that we interacted with all vari-ables; (b) on a partially restricted model, in which theonly difference from the model in (a) was that the coef-ficient on novelty-centered business model design wasrestricted to be the same for 1999 and 2000. Then,we did F-tests to test the null hypothesis of homo-geneity of the coefficient on design novelty in mod-els (a) and (b). Following Gatignon (2003, p. 74) the

test statistic we used was PRSS CUSS/DF_PRDF_CU/CUSS/DF_CU, where PRSS was the sumof squared residuals from the partially restricted model,CUSS was the sum of squared residuals from the com-pletely unrestricted model, DF_PR was the number ofdegrees of freedom of the partially restricted model, andDF_CU was the number of degrees of freedom of thecompletely unrestricted model. As a result of these tests,we could not reject the null.

Hypothesis 3 (about efficiency-centered business modeldesign) receives mixed support from our data. The resultsin Table 3 indicate that Hypothesis 3 is supportedby the Q4 2000 results in the full sample (Table 3b:

Models 14). The results are robust across all depen-dent variables (see Table 3c). In our full sample, dur-ing a period of resource scarcity, entrepreneurial firmsperformed better if their business model designandhence value proposition to their customers, partners,and suppliersincluded efficiency enhancements thatreduced their transaction costs, simplified transactions,and sped up processes. However, Hypothesis 3 is notsupported by the data pertaining to Q4 1999. Table 3a,which depicts the regression results during a period ofenvironmental munificence (1999), shows that while the


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Table 3a Mean-Centered OLS Regression Results (Full Sample)

Dependent variable Ln(market value Q4 av. 1999)

Model 1 Model 2 Model 3 Model 4

RHS variables Value (std. err.) Value (std. err.) Value (std. err.) Value (std. err.)

Constant 1975 1725 1978 1751

Design efficiency 128109 093090 128109 101090Design novelty 332 093 229 083 321 093 217 083

Interaction between design 828763 916609

efficiency and design novelty

Complementarities 063 059

Lock-in 080 051

Competition 005 008

Log(market size) 016 016

Age 005 005

Log(employees) 065 064

Country 012 020

R&D expenditure 1999 008 009

Advertising expenditure 1999 003 003

Capital expenditure 1999 000 000

R-squared 010 052 011 053

AdjustedR-squared 009 048 009 049F 847 1327 604 1253

N 158 158 158 158

001 p < 005, p < 001, p < 0001.

Table 3b Mean-Centered OLS Regression Results (Full Sample)


Model 1 Model 2 Model 3 Model 4

RHS variables Value (std. err.) Value (std. err.) Value (std. err.) Value (std. err.)

Constant 1842 1636 1844 1664

Design efficiency 221 118 244 101 216 110 251 101

Design novelty 172 101 154 093 170 101 147093

Interaction between design 824845 1025683efficiency and design novelty


Lock-in 030 057

Competition 088 104


Age 001 001


Country 112 101




R-squared 004 047 005 048

AdjustedR-squared 003 044 003 044

F 384 1259 288 1188

N 180 180 180 180

001 p < 005, p < 001, p < 0001, 005p < 01

coefficient of the mean-centered design efficiency vari-

able is positive, it is not significant. During this period of

abundant resources, efficiency-centered business model

design did not contribute to any significant differentia-

tion between entrepreneurial firms.

There is also a lack of support for this hypothe-

sis from the regressions done on the restricted sample

(see Table 3d). The coefficient on design efficiency is

insignificant in the restricted sample for each of the

models we ran, yet as noted above, it is significant in

the full sample for Q4 2000. What accounts for this

difference? We probed deeper into the underlying rea-

sons by running a separate set of regressions using only

those 30 firms that entered the sample in 2000. We


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Table 3c Summary of Main Regression Results for Different Dependent Variables

Independent variable Dependent variable Model 1 Model 2 Model 3 Model 4

1999 Design efficiency Market value Q4 close 170 135 170 144

Market value Q4 average 123 093 123 101

Market value annual average 125 089 125 096

2000 Design efficiency Market value Q4 close 276 316 270 326



1999 Design novelty Market value Q4 close 344 261 334 249



2000 Design novelty Market value Q4 close 128 177 123 166



001 p < 005, p < 001, p < 0001, 005p < 01

Table 3d Mean-Centered OLS Regression Results (Restricted Sample)


Model 1 Model 2 Model 3 Model 4RHS variables Value (std. err.) Value (std. err.) Value (std. err.) Value (std. err.)

Constant 1979 1725 1981 1750

Design efficiency 089112 057093 091112 068 093

Design novelty 356 097 251 087 346 097 240 087

Design efficiency design novelty 634778 759 618


Lock-in 037 013

Competition 003 015


Age 005 005


Country 021 028


Advertising expenditure 1999 002 002Capital expenditure 1999 000 000

R-squared 011 054 011 055


F 825 1270 571 1189

N 142 142 142 142


Constant 1842 1595 1843 1616

Design efficiency 136132 157109 137132 167 109

Design novelty 297 113 283 102 293 113 274 102

Design efficiency design novelty 239913 68 717


Lock-in 204 225

Competition 051 061

Log(market size) 003 004Age 001 001


Country 043 036




R-squared 007 052 007 053


F 488 1174 325 1090

N 142 142 142 142

001 p < 005, p < 001, p < 0001, 005p < 01.


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Table 4 Chow Test for Structural Break Between 1999 and

2000

Dependent variable Model 1 Model 2 Model 3 Model 4

Market value Q4 close 341 1492 2569 1406


Market value annual 248 193 195 187

average

Notes. Table entries are F-statistics.001 p < 005, p < 001, 005 p < 01

observed that these firms had significant positive coef-ficients for efficiency-centered business model design in2000, which were also significantly different from therespective coefficients in the restricted sample in 1999(according to the t-test suggested by Cohen and Cohen1983, p. 111). This may have strengthened the designefficiency effect in the full sample.

This analysis highlights the role of entry dynamics.

Under low resource munificence, capital markets may bemore receptive to new public offerings from firms thatpromise lower transaction costs. This in turn may favorthe IPOs of firms that have more efficiency-centeredbusiness model designs. Overall, however, Hypothesis 4has little support from our empirical analysis. Whilethe Chow test suggests a structural break in the overallmodel parameters between 1999 and 2000 (see Table 4),and while Table 3c suggests a strengthening of thedesign efficiency effect from 1999 to 2000, a series ofpooled regression analyses with dummy variables (seealso Gatignon 2003, p. 74) did not allow us to reject thenull hypothesis that the coefficient on design efficiency

was identical in 1999 and 2000.5Hypothesis 5 (about the interaction effect among the

design themes of business models) received no sup-port from the empirical analysis: None of our regres-sions revealed a significant positive interaction. Indeed,the coefficient of the variable capturing the interactionbetween design novelty and design efficiency had a neg-ative sign in all the regressions we ran, yet in most casesit was not statistically significant (see Tables 3a, 3b, and3d). That coefficient, however, was significant at the 10%level in Model 4 for the full sample when we used thelogarithm of the market value of firms at the close of Q42000, and the logarithm of the average market value of

firms in 2000, as dependent variables. For these modelswe performed post hoc analysis using plotting techniquessuggested by Aiken and West (1991). The plots of designefficiency on the respective dependent variable for differ-ent values of design novelty revealed that for higher val-ues of design novelty, the slope of the plotted regressionline was smaller, but remained positive. In other words,the plot was consistent with Hypothesis 6 and yieldedthe additional insight that while diseconomies of scopein design might exist, they do not override the positiveeffects of efficiency-centered design on performance. Our

analysis of novelty-centered design yielded analogousresults. Our data seem to suggest, yet do not convincinglyprove, that there appear to be diseconomies of scope indesign; that is, attempting to emphasize both efficiencyand novelty in the design of a business model may becostly and could adversely affect performance. Our anal-

ysis provides preliminary, albeit statistically weak, sup-port for Hypothesis 6.

Discussion and ConclusionThe central thesis anchoring our study is the notionthat organizational design should extend beyond internaldesign (Nystrom and Starbuck 1981) to include a focuson the architecture of the transactions that a focal firmengineers with its partners, suppliers, and customers.Consistent with Foss (2002), we suggest the need topay greater attention to the structuring of firm bound-aries and, in particular, to the structuring of a firms

exchanges with external stakeholders. We develop a the-ory of business model design that explains how valueis created at the business model level of analysis andhow it is captured at the focal firm level of analysis. Noprior theory explicitly centered on this issue exists. Ourtheoretical contribution is the model that links businessmodel design to performance of entrepreneurial firmsunder varying conditions of environmental munificence.

Although the design of the business model has beenraised as an important issue for research on new orga-nizational forms and boundary-spanning organizationaldesigns (Foss 2002, Rindova and Kotha 2001), it has notbeen explored in detail. Perhaps this is because, until

now, we lacked a methodology for conceptualizing andmeasuring business model design with a high degreeof granularity. Our methodological contribution is thatwe provide a way to think about, and measure, busi-ness model design themes. By moving beyond generictypologies of business models (which are often onlyapplicable to e-commerce firms), we offer a greater levelof abstraction and a higher degree of granularity in thedescription and measurement of business model designs.This allows us to outline the design elements of busi-ness models that are relevant for wealth creation, andit also allows us to provide measures that can be moregenerally applied to entrepreneurial firms.

Our research is particularly relevant to the study ofnew organizational forms, innovation, and entrepreneur-ship. It adds to an emerging body of research on busi-ness models (e.g., Amit and Zott 2001, Chesbroughand Rosenbloom 2002, Hargadorn and Douglas 2001,Mendelson 2000). We operationalize and measure thebusiness model construct, and show empirically that ithas an impact on wealth creation. To the best of ourknowledge, this is the first rigorous empirical large-sample study of business model design themes. Whilethere are promising empirical studies in this domain


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(e.g., Rajgopal et al. 2003), there has been no systematiclarge-scale empirical analysis of the performance impli-cations of business model design themes under variousenvironmental regimes.

By providing common definitions for new organiza-tional forms (particularly boundary-spanning designs),

our study suggests design options and enables com-parisons among different designs, enhancing the scien-tific base of organization design (Dunbar and Starbuck2006). It can also help bridge the growing gap betweenthe reality of organization design and organization the-ory that some scholars have identified (e.g., Daft andLewin 1993, Ilinitch et al. 1996). While organizationscholars have investigated intriguing, yet largely iso-lated, cases of new organizational forms, such as thedynamic network (Miles and Snow 1986), the virtualcorporation (Davidow and Malone 1992), or hypertextorganizations (Nonaka and Takeuchi 1995), research onthese designs could be unified and advanced through

common frameworks, concepts, and theories (Daft andLewin 1993, Foss 2002). Our study shows that captur-ing configuration as variables helps us characterize andmeasure business model designs, which should facilitatefurther research in that area.

This paper articulates essential features and proper-ties of boundary-spanning organizational designs, andaddresses their performance implications. Our strongestand most robust finding relates to the novelty-centeredbusiness model design. This centers on innovation,which is the specific instrument of entrepreneurship. Itis the act that endows resources with a new capacity tocreate wealth (Drucker 1985, p. 30). Wealth-creating

innovation may be achieved through a recombination ofexisting resources (Schumpeter 1934) in new designs.Our study shows that firms can innovate not only byrecombining the resources they control, but also by har-nessing those of the partners, suppliers, and customerswho participate in their business model. In this way, ourstudy contributes to the entrepreneurship literature. Wehighlight business model design as a crucial task forentrepreneurs, and as a source of innovation. We alsofind that environmental munificence does not moderatethe positive relationship between business model designinnovation and focal firm performance. This counterin-tuitive finding is noteworthy. It attests to the remarkable

temporal stability of that relationship, emphasizing thebusiness model as an important and enduring locus ofinnovation and wealth creation.

By framing business model design as an entre-preneurial task, and by identifying business model inno-vation as a source of wealth creation for firms, ourwork informs research at the intersection of organizationtheory, entrepreneurship, and strategy (Hitt et al. 2001,Langlois 2005). Business model-specific effects mayaccount for some hitherto unexplained variance in theperformance of firms. In this sense, they complement,

but do not replace, firm-specific and industry-specificeffects on firm performance (Rumelt 1991, Hawawiniet al. 2003, McGahan and Porter 2002). We corrobo-rate the premise that in a highly interconnected world,entrepreneurs should consider looking beyond firm andindustry boundaries in order to create and capture busi-

ness opportunities. They can create wealth by introduc-ing innovative boundary-spanning organization designs.

We acknowledge several limitations of this study.Some empirical results could be affected by measure-ment problems. For example, our measurement of busi-ness model design themes may not have captured all thelines of a firms business that have revenue potential,and therefore might not explain all the variation in thedependent variable due to business model design themes.Another problem could be that bad management corruptsinherently good designs. Unfortunately, our data do notallow us to control for the quality of management. Data

limitations alo prevent us from engaging in a dynamicanalysis of business model evolution or measuring valuecreation directly at business model level. Last, the scopeof the theory presented in this paper, and the data setused to test it, do not allow us to draw generalizableconclusions about the role of business model designs inthe broader population of firms.

From an entrepreneurial standpoint, however, the lim-itations of this study could present interesting opportu-nities for future research. For example, do our resultsapply to more mature and established organizations?What factors give rise to and shape business model de-signs? How do regulations, customer preferences, and

competition influence the emergence and evolution ofthese designs? What are the dynamics of business modeldesign change, and how stable are business modeldesigns across time? How reliable is the impact ofvarious business model design themes on performance,and do efficiency-centered business models have higherreliability of performance than novelty-centered ones(Sorensen 2002, Sorenson and Sorensen 2001)? Organi-zation scholars might be particularly interested in howthe firms architecture of boundary-spanning transactionsis linked to its internal organization and how the interac-tion of the two affects firm performance. Strategy schol-

ars could be interested in whether business model designcontributes to the competitive advantage of firms, andhow it interacts with firm strategies, such as productmarket positioning.

We hope that the ideas presented in this paper willinspire and enable further research on these intriguingissues. We believe that the perspective of the businessmodel, its design elements, and the concepts developedhere for describing and measuring business model designthemes are a step toward an improved understanding ofboundary-spanning organizational designs.


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AcknowledgmentsBoth authors contributed equally to this article. Christoph Zottgratefully acknowledges financial support from the AllianceCenter for Global Research & Development and the Rudolfand Valeria Maag Fellowship in Entrepreneurship. Raffi Amitacknowledges the generous financial support of the Whartone-business initiative (a unit of the Mack Center for Techno-

logical Innovation at The Wharton School), and the RobertB. Goergen Chair in Entrepreneurship at The Wharton School.Both authors thank Iwona Bancerek, Amee Kamdar, andJenny Koelle for their research assistance. They are grate-ful to Senior Editor Rich Burton and to two anonymousreviewers for helpful comments. For insightful comments dur-ing the development of this study, the authors would like tothank Eric Bradlow, Hubert Gatignon, Lorin Hitt, Ha Hoang,Quy Huy, Aba Krieger, Anita McGahan, Werner Reinartz,Nicolaj Siggelkow, Belen Villalonga, and seminar participantsat Washington University in St. Louis and at The WhartonSchool.

Appendix A. Survey Items

Survey item Scale*

Efficiency-centered business model designInventory costs for participants in the business model are reduced. SA, A, D, SD

Transactions are simple from the users point of view. SA, A, D, SD

The business model enables a low number of errors in the execution of transactions. SA, A, D, SD

Costs other than those already mentioned for participants in the business model are reduced SA, A, D, SD(i.e., marketing and sales costs, transaction-processing costs, communication costs, etc.).

The business model is scalable (i.e., can handle small as well as large number of transactions). SA, A, D, SD

The business model enables participants to make informed decisions. SA, A, D, SD

Transactions are transparent: Flows and use of information, services, goods can be verified. SA, A, D, SD

As part of transactions, information is provided to participants to reduce asymmetric degree SA, A, D, SDof knowledge amongst them regarding the quality and nature of the goods being exchanged.

As part of transactions, information is provided to participants about each other. SA, A, D, SD

Access to large range of products, services, information, and other participants is provided. SA, A, D, SD

The business model enables demand aggregation. Y, N

The business model enables fast transactions. SA, A, D, SD

The business model, overall, offers high transaction efficiency. SA, A, D, SD

Novelty-centered business model designThe business model offers new combinations of products, services, and information. SA, A, D, SD

The business model brings together new participants. SA, A, D, SD

Incentives offered to participants in transactions are novel. SA, A, D, SD

The business model gives access to an unprecedented variety and number of participants SA, A, D, SDand/or goods.

The business model links participants to transactions in novel ways. SA, A, D, SDThe richness (i.e., quality and depth) of some of the links between participants is novel. SA, A, D, SD

Number of patents that the focal firm has been awarded for aspects of its business model. 0, 12, 34,>4

Extent to which the business model relies on trade secrets and/or copyrights. R, S, B, N

Does the focal firm claim to be a pioneer with its business model? Y, N

The focal firm has continuously introduced innovations in its business model. SA, A, D, SD

There are competing business models with the potential to leapfrog the firms business model. SA, A, D, SD

There are other important aspects of the business model that make it novel. SA, A, D, SD

Overall, the companys business model is novel. SA, A, D, SD

SAStrongly Agree (coded as 1); AAgree (0.75); DDisagree (0.25); SDStrongly Disagree (0); YYes (1), NNo (0); RRadically

(1); SSubstantially (0.66); Ba bit (0.33), Nnot at all (0); 0 (0), 12 (0.33), 34 (0.66), >4 (1).

Appendix B. Convergent and Discriminant ValidityWe first ran a confirmatory factor analysis (CFA) on a mea-surement model with two factors, where the design efficiencytraits loaded onto the design efficiency factor, and the designnovelty traits loaded onto the design novelty factor. In thismodel, the correlation between the design efficiency and thedesign novelty index was estimated. We then ran a CFA on

a measurement model with only one factor, where the corre-lation between the design efficiency and the design noveltyvariable was constrained to be one. If the model where thecorrelation is not equal to one improves the fit significantlycompared to the constrained model, the two constructs (i.e.,design novelty and design efficiency) are distinct from eachother, although they can be significantly correlated (Gatignonet al. 2002, Gatignon 2003).

We also used CFA to establish the convergent validity ofthe constructs, by comparing a measurement model where thecorrelation between the two constructs was estimated with amodel where the correlation was constrained to be equal to


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Table B.1 Confirmatory Factor Analysis

Correlation Chi-squared Degrees of freedom

0.14 733.4 319

0 735.1 320

1 761.9 320

zero. A significant improvement in fit indicates that the twoconstructs are indeed related, which confirms convergent valid-ity (Gatignon et al. 2002, p. 1109).

We used LISREL to implement the CFA, following the rou-tines described in Gatignon (2003, pp. 178220). The resultsfrom the CFA are displayed in Table B.1.

The results from the CFA demonstrate that efficiency-centered design and novelty-centered design are two distinctdimensions of business models, although they are positivelycorrelated (estimated correlation= 014). This is confirmed bya significantly (at the 0.01 level) improved confirmatory factoranalytic model when the correlation is estimated, compared toa measurement model where the correlation is constrained to1 (chi-squared= 7619 7334 = 285, degrees of freedom =320319= 1). Furthermore, the results from the CFA demon-strate that efficiency-centered design and novelty-centereddesign are independent dimensions of business models. Theconfirmatory factor analytic model when the correlation isestimated, compared to a measurement model where the cor-relation is constrained to zero, is not significantly improved(chi-squared = 7351 7334 = 17, degrees of freedom=320 319 = 1). This is akin to the Gatignon et al. (2002)result that some dimensions of innovation (e.g., competence-enhancing/destroying) are independent of others (e.g., radical-ness), yet all measure important, distinct aspects of innovation.

In addition to CFA, the literature suggests partial least

squares (PLS) as another method for assessing discriminantvalidity. Using PLS, one can determine whether a constructshares more variance with its measures than it shares withother constructs in the model (Hulland 1999, Reinartz et al.2004). This is achieved (1) by calculating the square rootsof the average variance extracted (AVE) values, which mea-sure the average variance shared between a construct and itsmeasures, and (2) by calculating the correlations between dif-ferent constructs. A matrix can then be constructed where thesquare root of AVE is in the diagonal, and the correlationsbetween the constructs are in the off-diagonal. For adequatediscriminant validity, the diagonal elements should be greaterthan the off-diagonal elements in the corresponding rows andcolumns (Fornell and Larcker 1981). In our case, we obtained

Table B.2 Partial Least Squares Analysis

Design efficiency Design novelty

Design efficiency 0, 233 0, 175

Design novelty 0, 175 0, 243

Notes. (1) The square root of AVE is displayed in the diagonal,

and the correlations between the constructs are displayed in the

off-diagonal. (2) According to Fornell and Larcker (1981), if the fac-

tor variance is set to one, then the average variance extracted is

defined as: AVE =

2i/

2i+

12i.

the matrix depicted in Table B.2 as a result of the PLS analy-sis. The results further strengthen the discriminant validity ofour constructs.

Endnotes1There are many studies that examine a range of issues relat-ing to the conduct and performance of e-commerce firms

that became publicly listed corporations during the late 1990s(see, for example, Rajgopal et al. 2002, 2003; Kotha et al.2004). Put together, these and related studies provide impor-tant insights into the type of firm we investigate in this paper.Data limitations prevented us from using Heckmans techniqueto correct for potential survival bias.2Overfitting occurs when the fit of the model with the datais due to the idiosyncrasy of a specific data set. We tooka random subsample of 150 firms, with the remaining firmsconstituting the holdout sample, then calibrated the modelbased on the subsample and applied the resulting parameterestimates to the holdout sample, calculating goodness-of-fit,pseudo F-value, and Theil U statistic.3To use the truncated regression model (see Maddala 1986),

we assume that private entrepreneurial firms have smaller mar-ket values than public ones. We find that the coefficient esti-mates from the truncated regression are analogous to the OLSestimates. The Wald test in the truncated regression, and theF-statistic in the OLS regression, are both significant at the5% level for all models.4An appendix that describes the method is available on requestfrom the authors.5These results also fail to support the idea that capital mar-kets valued novelty- versus efficiency-centered business modeldesigns differentially before and after the stock market crashon NASDAQ in April 2000 due to irrational assumptions. Wewould like to thank one reviewer for this insight.

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