innovation alignment and project network dynamics: an integrative model for change

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22 September 2007 � Project Management Journal � DOI: 10.1002/pmj 22 September 2007 � Project Management Journal � DOI: 10.1002/pmj

INTRODUCTION �

Researchers investigate implementation processes and diffusion out-comes for innovations to both understand and improve their mar-ket acceptance rates. Organizational innovation research to datehas predominantly focused on hierarchically organized bureau-

cratic organizations competing within the context of single markets. Afuah(2001), a notable exception, observed how an innovation in reduced instruc-tion set computing (RISC) impacted efficient buyer-supplier organizationalboundaries. He concluded that innovation studies are incomplete if they donot look beyond focal firms. A growing body of organizational researchexplores a relatively new form of organization, the interorganizational proj-ect network. Firms in project networks distribute work processes acrossorganizational boundaries and interdependent specialist firms execute workon projects. More than a decade has passed since researchers of these orga-nizational networks first exposed the proliferation of this form of organiza-tion vis-à-vis traditional hierarchies (Barley, Freeman, & Hybels, 1992;Kanter, 1991; Pekar & Allio, 1994). Given the growth in the formation of proj-ect networks, coupled with a parallel exponential growth in the number ofjournal articles on the subject of organizational networks in recent years(Borgatti & Foster, 2003), it is surprising that innovation scholars have large-ly ignored this organizational development.

With a burgeoning literature on project-based interorganizational net-works, we might expect project network researchers themselves to explorethe subject of innovation. For a quarter of a century, network researchershave studied the economic (Eccles, 1981; Williamson, 1975, 1985) and socio-logical (Granovetter, 1985; Powell, 1990; Uzzi, 1997) foundations of the net-work form of organization. Though there is general agreement amongresearchers that organizing into project networks leads to improved per-formance (Gulati, 1995; Hamel, 1991; Powell, Koput, & Smith-Doerr, 1996),only a handful of studies discuss the implications of project network organ-izations on innovation; and none of those that do link network processes toinnovation outcomes.

This biased trend in the network literature led Podolny and Page (1998, p. 73) to suggest that this literature “runs the risk of succumbing to a naïvefunctionalism.” However, upon a closer examination of this literature, weidentify a growing discord among network researchers on the subject ofinnovation. One cluster of researchers focuses on the ability of a network of firms to produce novelty. In an investigation of biotechnology project net-works, Powell and his colleagues (1996) concluded that the project networkitself can be viewed as the locus for innovation and learning. Ahuja (2000)confirmed Powell et al.’s findings in chemical industry networks. In contrast,

ABSTRACT �

Innovation research has predominantlyfocused on hierarchically organized firms com-peting within single markets. Recently, howev-er, researchers have debated over whether theincreasing use of project networks within andacross industries promotes or stifles innova-tion. This paper discusses a model based on cross-national diffusion data from threetechnological innovations in three-dimensionalcomputer-aided design (3D CAD) and relatedimplementation data from 82 firms. From thedata we induce a set of constructs that form the basis of a two-stage model for understand-ing innovation in project networks. In the firststage of the model the alignment of an innova-tion to the existing allocation of work in a proj-ect network is ascertained. In the second stage,the implementation success and diffusion out-comes for innovations misaligned with the allo-cation of work are governed by the relationalstability, accrual of interests, boundary perme-ability, and existence of an agent for projectnetwork change. In developing this integrative,two-stage model we resolve the contradiction inthe academic literature regarding the degree towhich project network dynamics can promote orstifle innovation.

KEYWORDS: 3D CAD; innovation diffusion;project network dynamics; technology implementation

Project Management Journal, Vol. 38, No. 3, 22–35

© 2007 by the Project Management Institute

Published online in Wiley InterScience

(www.interscience.wiley.com)

DOI: 10.1002/pmj.20003

Innovation Alignment and ProjectNetwork Dynamics: An IntegrativeModel for ChangeJohn E. Taylor, University of Texas at Austin, Austin, TX, USARaymond Levitt, Stanford University, Stanford, CA, USA

September 2007 � Project Management Journal � DOI: 10.1002/pmj 23

other researchers identify concomitantissues for innovation associated withlearning in project networks. Lampeland Shamsie (2003, p. 2206) cautionedstrongly against the use of project-basednetworks, finding an “evolutionarystagnation in the craft of makingmovies” associated with the adoptionof the project network form of organi-zation in the Hollywood motion pictureindustry. Gann and Salter (2000) identi-fied broken learning and feedbackloops in construction industry projectnetworks that negatively impactedinnovation capabilities. Taylor andLevitt (2004) later identified similarlearning issues relating specifically tothe implementation of innovations thatimpact multiple firms in constructionproject networks.

Given the widespread adoption ofproject networks as a form of industrialorganization, it is critical that paradox-ical interpretations of networks as “locifor innovation” or as paths to “evolu-tionary stagnation” be resolved. In thispaper the implementation processes isinvestigated for three comparable inno-vations in three-dimensional comput-er-aided design (3D CAD) software. Welink the observed implementationprocesses to market level diffusion out-comes in the U.S. and Finland. Inte-grating perspectives across levels ofanalysis we induce a grounded theoret-ical model for understanding innova-tion in the context of project networkdynamics.

Research Setting andMethodologyConstruction Industry ProjectNetworksEarly research on project networksfocused on the construction industry.Eccles (1981) introduced the notion of“quasifirms” into the literature todescribe organizational arrangementshe observed in the Massachusettsbuilding industry. Interorganizationalnetwork researchers typically point toconstruction as exemplifying the project

network form of organization (Powell,1987, 1990). The construction industryis a mature industry that has beenorganized into networks since the1950s (Stinchcombe, 1959). Many ofthe industries being investigated inproject network research are relativelynew, having adopted the network formof organization in the 1990s (Lampel &Shamsie, 2003). Because our goal wasto observe process changes broughtabout by the implementation of a newtechnology, the maturity and stabilityof construction industry project net-works enabled us to transparentlyobserve process variations resultingfrom the implementation of the inno-vations in CAD software.

In most cases, the project networkswe researched consisted of an owner,an architect, an engineer, a generalcontractor, numerous subcontractors(e.g., plumbing, HVAC, electrical, andframing), and fabricators. We definethe project network as the group ofspecialist firms contracted to worktogether on specific constructionprojects. We view projects as instancesof work for the network. Examples ofprojects in the context of this paper include the design and construc-tion of a building, the design andfabrication of a structural system for abuilding, or the design and construc-tion of a home.

We introduced variation into ourresearch design by focusing on net-works in two distinct markets. Glaserand Strauss (1967) suggested that max-imizing variances in research designsenables researchers to develop densecategories and identify fundamentaluniformities. Because we lack a foun-dation of research and constructs at theintersection between innovation andproject network research, we designeda cross-national investigation to capi-talize on national variances to identifyrelevant constructs and dimensions. Inthe Hall and Soskice (2001) study ofvarieties of capitalism, Finland wasidentified as a coordinated market

economy (e.g., particularistic, withlong-term relationships) and the U.S.as a liberal market economy (e.g., uni-versalistic, arms-length relationships,and one-off contracting).

The “varieties of capitalism”approach is a relevant dimension uponwhich to introduce variance. The defi-nition of liberal vs. coordinated marketeconomies implies some variation ininter-firm relationships across coun-tries. Consequently, we chose to con-centrate our data collection efforts on construction industry project net-works in the U.S. and Finland (thoughsome important, anecdotal evidence isalso included in studies from Franceand Germany) on the basis that theyprovided “polar” contrasting cases(Pettigrew, 1990). Firms in project net-works selected for inclusion in thestudy were chosen on the basis of theirability to support analytic generaliza-tion (Yin, 1989). In other words, specif-ic networks were selected that were in the process of implementing one ofthe three 3D CAD software applicationsinvestigated in the study.

3D CAD Technological Innovations InvestigatedOur data collection efforts focused onthree comparable technological inno-vations in the construction industry.Software vendors in the industry rec-ently introduced a three-dimensional,object-based modeling version of computer-aided design software thatenables architects, engineers, contrac-tors, subcontractors, and fabricators towork together to build shared, three-dimensional computational models ofbuildings. This new functionality is described in the industry as “virtualdesign and construction,” “model-based design,” and “building informa-tion modeling” applications. We referto this new generation of software as3D CAD software. In the 1980s, earlyCAD software enabled the digital repre-sentation of a building through two-dimensional line drawings on personal

24 September 2007 � Project Management Journal � DOI: 10.1002/pmj

Innovation Alignment and Project Network DynamicsP

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computers. By the 1990s, some vendorsbegan introducing CAD software packages that allowed for sophistica-ted design and representation of three-dimensional geometries and relateddata. Only recently, however, havemainstream CAD software vendorsbegun marketing object-orientedbuilding information modeling sys-tems that seamlessly integrate 3Dgeometry at the building componentlevel with a wide variety of data.

The evolution from paper-baseddrafting to two-dimensional, line-based CAD required a change in workpractices within the organization.Different firms in a network couldadopt this practice within their firm’sboundaries without changing theirinterdependencies with other special-ists in the network. Firms continued toexchange sets of plans as blueprints.This meant early adopters of CAD tools could still interact in much thesame way with others who still produced drawings manually. The evolution from two-dimensional line-based CAD to three-dimensional CAD geometries had a similarly localizedeffect. Exchange of information contin-ued to be enacted, for the most part,through exchange of paper-based blue-prints. The three-dimensional viewswere used primarily by architects tobetter illustrate designs to owners andwere not exchanged electronically withother specialists in the project network.

In contrast to these two prior inno-vations, the more recent evolution fromthree-dimensional CAD geometries to three-dimensional building infor-mation models creates new interdepen-dencies and collaboration requirementsfor firms in the project network withoutgreatly altering the end product (e.g., aset of blueprints). Researchers havedescribed these systemic innovationsas potentially leading to significantincreases in productivity while beingparticularly difficult to implement inproject networks (Taylor & Levitt,2004), particularly when the technolo-gies span organizational boundaries

(Taylor, 2007). In our study, we focus onthree specific 3D CAD applications.Because we used theoretic replicationlogic (Yin, 1989) to select “polar” net-works, literal replication logic to choosethree similar innovations (Yin, 1989).Our expectation was that the imple-mentation findings for the three 3DCAD applications would not vary sig-nificantly within a single market, whichenabled us to focus on the variancesintroduced by different market struc-tures while maintaining consistencyacross the technologies introduced. Byincorporating literal and theoreticreplication logic strategies to ourresearch design, the external validity ofour findings (Yin, 1989).

The first innovation we studied,which we will refer to as BuildingModeler, was developed by a globalsoftware firm that while based in theU.S. also has sales and developmentoffices in Europe. They focus their mar-keting and development efforts largelyon the needs of architects. The second3D CAD application in our study, whichwe will refer to as Structural Modeler, isproduced by a global software develop-ment firm based in Finland that targetsits product development and marketingto structural engineers. This firm also has offices in the U.S. We refer tothe third application included in our study as the Home Modeler. The com-pany that created Home Modeler operates in the U.S. through a sub-sidiary but is based in Finland. Its 3DCAD application targets the homebuild-ing market.

Data Collection and AnalysisResearchers recommend that ground-ed theory-building research includemultiple case studies (Eisenhardt,1991) and multiple data collectionmethods (Eisenhardt, 1989) in order toincrease the validity of the constructsidentified. In this paper we investigatethree innovation cases diffusing throughproject networks in the U.S. andFinland. We employ multiple data collection methods, including ethno-

graphic interviews, direct observation,and review of primary and secondarydocumentation. By triangulating ourfindings across these different data col-lection methods we strengthen thevalidity of our findings (Eisenhardt,1989).

The data collection effort for thispaper took place over a period of ninemonths. Three months were spent col-lecting data in Finland and the remain-ing six months were spent collectingdata in the U.S. We conducted morethan 200 hours of interviews in 82 discussions with owners, architects,engineers, general contractors, sub-contractors, and fabricators. Of theseinterviews, 31 were conducted at proj-ect network specialist firms in Finlandand the remaining 51 were conductedwithin the U.S. In most cases we inter-viewed the individual in the organiza-tion most involved in managing thecompany’s utilization of CAD prod-ucts. This individual typically held thetitle of CAD manager or CAD director.In some instances we spoke to moresenior managers. In all cases wefocused the interview discussion onspecific project experiences wheretransitions to 3D CAD applicationsoccurred.

In addition to the interviews, directobservations were made within andacross specialist firms to observe thechanges in process associated withimplementing the 3D CAD applications.We were invited to attend companymeetings and project discussions, to visitproject sites both under constructionand recently completed, and to generallyobserve the interactions between spe-cialists in the network relating to theimplementation of 3D CAD. We tookextensive notes during this process andtook digital photographs for use in ourdata analysis. The interviewees’ respons-es and our observations were recorded ina numbered set of field research note-books. The interviews were also recordedusing a digital voice recorder.

Whenever possible, we requestedhard copies of materials discussed

during interviews and noted duringobservations. Data collected includedcontract documents, process flow dia-grams, construction schedules, 3DCAD models, bills of materials, projectdecision schedules, animations ofbuilding information models, and anyother information that might lendinsight into the internal and inter-orga-nizational practices of the project net-work in its implementation of 3D CADapplications. We attached this primarydocumentation to our field notebooksand often found that it elucidated con-cepts that were not entirely clear whenwe reviewed the notes from an inter-view or observation. We also obtainedtemporary licenses for the 3D CADmodeling software from one of thethree vendors included in the study.This allowed us to develop a familiar-ization with the technology beingimplemented by the U.S. and Finnishconstruction project networks that weobserved in the course of this research.

The research also benefited frommany informal discussions withinformants who had a general perspec-tive on 2D and 3D CAD use in both U.S.and Finnish project networks. We wereable to attend a conference related to advanced 3D CAD modeling applica-tions in both the U.S. and Finland andwere able to speak to many users. In theinteractions with these informants andconference users, we were able to con-firm our findings and thereby validateour constructs. Overall, we were able tomanage the reliability of our findingsby keeping an indexed, organized data-base of our field notebooks, audiointerview files, photographs, and docu-ments collected.

The data collected in this projectwere entered into a qualitative dataanalysis software application. Datafrom the interviews, observation, docu-mentation, and photographs werecoded and systematically analyzed forpatterns. Memo notations were used todevelop concepts and constructs.Constructs were grouped into proposi-tions that explain the implementation

process in project networks. Finally, aset of propositions was developed toprovide the foundation for a groundedtheoretical model for innovation inproject networks.

Aligning Innovation andNetworksWe designed this research to compareinnovation acceptance across firm net-works within different countries. Thepurpose was to gain insight into howinnovations are implemented in anddiffuse through networks of firms.Some innovation research (Afuah,2001) finds that organizational bound-aries make adapting to an innovationand developing appropriate transitionstrategies difficult. Afuah (2001) con-cluded that innovation studies thatonly include focal firms are incomplete.In our research we found that the key tounderstanding innovation in networkslies in a finer-grained understanding ofhow work is allocated across bound-aries in networks and of role relationsbetween specialists in the network.

Allocation of Work to Specialistsin NetworksDuring the data collection in Finland,we were surprised to learn that work inthe project network there is allocated in a fundamentally different way fromnetworks in the U.S. In one interview wesought to understand how the firms inone Finnish network used the HomeModeler 3D CAD application. We werespecifically trying to determine whetherthe architect did the final detailing of thedesign or whether it was handled by thecontractor, subcontractor, or fabrica-tor. However, we were having a greatdeal of difficulty getting the intervieweeto understand the concept of “detailing.”

To resolve the situation, the inter-viewee firm invited a professionaltranslator into the meeting. After somedeliberation, the translator suggestedthat the problem in communicationwas due to the fact that a single verb,suunnitella, describes both the design-ing and detailing process in the Finnishlanguage. Furthermore, there is no

separate verb to describe the act ofdesigning or detailing. In Finnish workpractice, the designer always does thedetailing work. Therefore, the architectusing the Home Modeler applicationboth designs and details the model.

In contrast, work allocation in proj-ect networks in the U.S. using theHome Modeler application is quite dif-ferent. In the U.S., the architect is onlyexpected to provide a schematic designof the home. The downstream partnersin the network detail the design provid-ed by the architect. One architecturefirm in the U.S. describes architecturaldesigns as follows:

Design professionals don’t use exactdimensions. Contractors interpretthese (refers to the architect’s draw-ings) and create shop drawings withactual dimensions . . . if a dimensionis wrong, it’s the contractor’s fault.

To confirm the generality of this workallocation practice, we posed similarquestions to project networks in Finlandand the U.S. implementing the BuildingModeler and Structural Modeler applica-tions. The work practice of architectsproviding schematic designs in the U.S.and “detailed” designs in Finland wasalso true for the networks using theBuilding Modeler application. However,we found that users of the StructuralModeler application could be observedto allocate work in similar ways eventhough no architect was involved. AFinnish structural engineer describedthe process in Finland in this way:

The structural engineer is responsi-ble for the structural analysis (drawsa process flow diagram) which is aniterative process of assuming mem-ber sizing, applying loads, checkingdeformations, stresses and supportreactions. You check the codes andif everything is okay you do all the connection details, slot holes,connectors . . .

In contrast, fabricators completethe final detailing of schematicdesigns provided by structural engi-neers in the U.S. They are then able to




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adjust the connection details to matchtheir operations and available inven-tory. For example, a design mayrequire a certain member sizing andconnection detail, but in order to savetime and costs in the fabricationprocess, the fabricator might suggestusing a slightly larger member andbolt size to divest themselves of inven-tory surpluses. In the Finnish projectnetworks, this practice is much lesslikely since fabricators fabricate struc-tural materials to the exact, detailedspecification of the engineer.

This finding of differences in howwork is allocated to specialists was con-sistent within each national marketstructure and across the three innova-tions included in the study. Given thiscorroboration across the data set, weconsider the finding that work is consis-tently allocated differently— designerscomplete “detailing” work in Finlandbut not in the U.S.—across markets tobe significant. Though significant in thisstudy, the idea of different countrieshaving different approaches to technol-ogy and work is not new. Hughes (1983)published a comprehensive study of how differing technological styles pro-duced significantly distinct electrifica-tion systems in different countries. Wewill discuss the implications of thisfinding in a later section.

Project Network and InnovationAlignmentBuilding ModelerThe Building Modeler applicationreplaced existing technologies for con-ceptual architectural design and detail-ing with an integrated building infor-mation modeling package. In Finland,where project networks allocateddesign and detailing work to designers,this integrated technology diffusedmuch more quickly than in the U.S. Aninterviewee from the firm that createdthe Building Modeler applicationdescribed the situation as follows:

Internationally, acceptance of our

products seems to have a lot to do

with process. In Europe firms are

more model-oriented. Back home

in the U.S., firms are much more

geared toward drafting.

A Finnish architectural firm adopt-ing the Building Modeler applicationcould do so without changing the workcompleted by different specialists inthe network. The model-basedapproach of 3D CAD provided architec-ture firms in Finland with a single soft-ware application that reduced gaps,overlaps, and issues of file exchangebetween disparate applications withintheir firm. In the U.S., however, thedetailing of designs is done by a spe-cialist other than the architect in thenetwork. Adopting the BuildingModeler application meant either thatarchitects would need to specify build-ings in more detail or that downstreamspecialists in the network would needto adopt and use a similar modelingapplication. Because architect fees donot include the detailing work and archi-tects are not trained to provide detaileddesigns, architecture firms in the U.S.were slow to adopt Building Modeler. Inthe work allocation of U.S. project net-works, downstream specialists couldgain value from the Building Modelerapplication, but because it only affecteda portion of the work allocated to themthey also were hesitant to adopt it.

Comparing market acceptance forthe Building Modeler application in theU.S. and Finland we observed a distinctdifference. The Building Modeler inno-vation was aligned with the existingallocation of work to specialists in theFinnish project networks. The BuildingModeler innovation integrated andimproved work already being complet-ed by Finnish architecture firms. Incontrast, the Building Modeler innova-tion was misaligned with the allocationof work to specialists in project net-works in the U.S. The application pro-vided more functionality than wasrequired by the architects and insuffi-cient functionality for the affecteddownstream network partners. Though

the Building Modeler vendor would notdisclose exact diffusion figures, theyprovided a telling anecdote about thediffusion of their product in the alignedFinnish market versus the misalignedU.S. market. The firm had projected,based on their experience with previ-ous product introductions of more lim-ited scope, a certain level of marketpenetration in each of these two mar-kets. To their surprise, the BuildingModeler innovation far exceeded pre-dictions of diffusion in the Finnishmarket. Conversely, in the U.S. marketthe Building Modeler innovation failedto realize predicted diffusion rates.

Structural ModelerThe Structural Modeler applicationsubstantially integrated the design,detailing, and fabrication of structuralmaterials in project networks. The levelof integration in the project network-required for this innovation meant thatthere would be some misalignmentwith both the U.S. and Finnish projectnetworks. In the U.S., the misalignmentin the allocation of work occurs at the interface between design anddetailing. In Finland, the misalignmentis at the interface between detailingand fabrication. Because project net-works in both countries contain mis-alignment between the innovation andthe allocation of work in the projectnetwork, the case of the StructuralModeler is particularly useful forexploring the variable impact of mis-alignment on diffusion outcomes.

An interviewee from the firm thatcreated the Structural Modeler applica-tion offered some illustrative datapoints for market acceptance of theirproduct in the U.S., Finland, France,and Germany. The product, which wascreated in Finland, achieved a nearly100% market penetration in Finlandover the period from the productlaunch in 1994 through 2004. In com-parison, in France and Germany(which adopt comparable strategies toFinnish networks for allocation of work)the Structural Modeler application

achieved a 60%–70% market penetra-tion in the period from 1996 to 2004. Insharp contrast, market acceptance forthe Structural Modeler application wasmuch slower in the U.S. In the periodfrom 1997 to 2004 the product achievedonly a 20%–30% market penetration inthe U.S., even in the relative absence ofcompeting products.

Home ModelerThe Home Modeler 3D CAD softwareapplication integrated the technolo-gies involved in design, detailing, andfabrication for home construction.Limited market adoption data wasavailable for the U.S. because the firmhad only recently begun marketing theHome Modeler application in the U.S.However, evidence from Finland clear-ly pointed to rapid market acceptanceof the Home Modeler innovation inspite of a structural misalignmentbetween the detailing and fabricationwork allocation in Finnish networks.Figure 1 summarizes the alignment ofeach 3D CAD technology investigatedwith regard to the allocation of work inproject networks in the U.S. andFinland.

The Impact of Alignment on DiffusionThe consistent findings across thethree 3D CAD innovation cases enablethe formulation of the followingproposition. We will treat the case ofmisalignment in more detail in the fol-lowing section.

Proposition 1. If an innovation isaligned with the allocation of work in aproject network, then it will diffusemore rapidly than if it is misalignedwith the allocation of work.

Misalignment and ProjectNetwork DynamicsBuilding Modeler provided a uniquecase in which the innovation wasaligned with the allocation of work inFinnish construction industry projectnetworks. However, the BuildingModeler in the U.S. and the Structural

and Home Modeler in both the U.S. and Finland were misaligned with the allocation of work. The impact of the misalignment on implementationprocesses innovation outcomes variedsignificantly between the U.S. and theFinnish project networks. In the follow-ing sections we describe a set of con-structs relating to implementation innetworks that moderated innovationoutcomes.

Relational StabilityIn Eccles’ (1981) 25-year-old study ofthe construction industry, he deter-mined that construction firms operatedin networks with long-term relation-ships and only contracted with one totwo firms for each type of specialty sub-contractor. These longer-term relation-ships were not based on choosing partners offering the lowest price andformed what Eccles termed “quasi-firms.” Interestingly, in our study, wefound that Finnish project networkscurrently contract very much along thelines described by Eccles, with firmsengaging in tight partnership relation-ships with one to three firms for eachspecialist type in the network. In con-trast, project networks in the U.S. cur-rently tend to adopt shorter-term relationships than those identified inEccles’ study. Interviewees in U.S. con-struction firm networks disclosed thatthey contract with five to six differentfirms for each specialist firm type.Many firms cited cost pressure as arationale for adopting a more arms-length approach to contracting. In the25 years since the Eccles’ investigationof the quasi-firm, the project networkhas evolved to shorter-term relation-ships with a larger set of partner firmsin the U.S.

We term the degree of stability innetwork role relations as relational sta-bility. Networks in the Finnish con-struction industry exhibited strongrelational stability by choosing to workwith only one to three firms for eachspecialist type. As predicted by the Halland Soskice (2001) study on varieties of

capitalism, members of networks inthis coordinated economy tended tochoose partners based on previousworking relationships. In contrast,project networks in the U.S. exhibitedweak relational stability due to the fact that members tended to choosefrom among five or six firms for eachspecialist type. Firms in the U.S. net-works were more concerned withgetting a low price than working withthe same set of firms from project toproject.

The relational stability constructrelates to several other constructsexplored in organizational research.For example, Stinchcombe (1968)described the process of having tosocialize new members in a group as the rate of social reconstruction.Interorganizational network researchersdescribe the phenomenon where firmsare socialized into networks as embed-dedness (Granovetter, 1985; Uzzi,1997). Though embeddedness is a mul-tifaceted concept, Granovetter descri-bes it in terms of on-going patterns ofrelations in economic exchange. This isconsistent with the Eccles (1981) conceptualization of the “quasifirm” in construction.

Each of the three innovationsachieved unexpectedly slow rates ofdiffusion in the U.S. In each of thesecases the innovation was misalignedwith the allocation of work in the U.S.project networks. Weak relational sta-bility in those networks created diffi-culties for firms implementing theseinnovations because knowledge gainedfrom one project failed to carry forwardto the next project when membershipin the project networks shifted signifi-cantly from project to project. Learningoccurred more slowly within firmsbecause the weak relational stabilitylimited the number of times they wereexposed to the innovation. However,much more insidious is the fact thatinter-firm learning—the developmentof interorganizational routines—failedto accumulate as a result of the limitedopportunities for specific specialist




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Design

Allocation of Work in the U.S.

Allocation of Work in Finland

Work to be Allocated toFirms in the Network

Designer

Detail Fabricate

Fabricator

Design S/W 2D CAD CAD/CAM

3D CAD technologicalinnovations and

alignment of the 3DCAD applications to

the allocation of workin each country

Technology Prior to3D CAD Innovation

Not Aligned to U.S. NetworkMisalignment exacerbated by

a set of moderating constructs

Aligned to Finish Network

Designer

Building Modeler Application

Not Aligned to U.S. NetworkMisalignment exacerbated by a set of moderating constructs

Not Aligned to Finish NetworkMisalignment mitigated by a set of moderating constructs

Structural Modeler Application

Not Aligned to U.S. NetworkMisalignment exacerbated by a set of moderating constructs

Not Aligned to Finish NetworkMisalignment mitigated by a set of moderating constructs

Fabricator

Home Modeler Application

Figure 1: Alignment of innovations to project networks in the United States and Finland.

firm pairs to work together. The impactof this has been explored in computa-tional simulation models (Taylor,Levitt, & Villarroel, 2006). Because eachof these innovations required firm net-works to shift the allocation of workand to resolve new kinds of interdepen-dencies, the weak relational stabilityexacerbated problems associated withimplementing the application in theproject network and led to much slow-er diffusion than expected.

In contrast, the strong relationalstability in the Finnish networks miti-gated the impact of misalignment ondiffusion for the Structural Modelerand Home Modeler innovations. Bothof these innovations diffused rapidlythrough the Finnish market. Becausethe Building Modeler innovation actu-ally was aligned to the allocation ofwork in the network, the relational sta-bility between firms was not an issueand the diffusion for that particularinnovation far exceeded the expec-tations of the firm that created theapplication. These findings enable the formulation of the following propo-sitions:

Proposition 2a. The weaker therelational stability in an interorganiza-tional network, the more difficult it is toachieve network-level learning. Thiscontributes to slower innovation diffu-sion rates.

Proposition 2b. The stronger therelational stability in an interorganiza-tional network, the easier it is to achievenetwork level learning. This contributesto faster innovation diffusion rates.

InterestsA second construct that varied betweenthe Finnish and U.S. network imple-mentation processes related to firm-level versus project-level interests. Inthe U.S., firms in project networks werefound to be focused on the interests oftheir own firm. In one illustrative case,an architecture firm in the U.S. optednot to inform its customers or networkpartners that it was using the Building

Modeler application even though itsmanagers acknowledged that sharingsuch information and files would great-ly reduce downstream workload andreduce errors. The architects statedclearly that they wanted the benefits ofthe new technology to accrue onlywithin their own firm. Firms in U.S.networks also expressed concerns overother firms exhibiting strategic, self-interested behavior. In other words,they were concerned that their tradingpartners would use the changerequired by shifting allocations of workto raise their pricing.

In the Finnish case, firms weremore inclined to share the benefits of3D CAD with their network partners. Inthe case of the Structural Modelerapplication, structural designers inproject networks in Finland chose toshare models with downstream fabrica-tors to obviate the fabricator’s need toproduce its own electronic CAD files formanufacturing. In the case of the HomeModeler innovation, one Finnish con-tractor described how it brought all ofits impacted network partners to sitaround a table and discuss how thechange would impact each firm, so thatthe costs and benefits of the innovationcould be equitably distributed acrossthe network.

Williamson (1985) discussed inter-ests in his work on transaction cost eco-nomics and economic exchange. Hedescribed hybrid forms of organizationas relying on “mutual interests”(Williamson, 1985, p. 155) to minimizetransaction costs by limiting the impactof opportunism and mistakes. The concept of interests also relates to the embeddedness construct describedby Granovetter (1992) and related to our relational stability construct.Granovetter argued that the deeper theembededdness, the more likely firms ina network are to see their interests asaligned rather than opposed. This isconsistent with what we observed inthe U.S. and Finnish networks.

When interests accumulated at thefirm level, as was the case for the U.S.

networks studied, the effect was toexacerbate the impact of misalignmenton diffusion. By considering only theirinterests and not attempting to sharethe benefits of the innovation withtheir trading partners, firms in U.S.networks were restricting the rate ofdiffusion of the innovation. In contrast,in the Finnish networks the interestswere defined at the network level, alle-viating fears of opportunism andincreasing firms’ willingness to share thebenefits of innovation with their part-ners. In these networks, the network-level accrual of interests mitigated theimpact of misalignment on diffusion.These findings enable the formulationof the following propositions:

Proposition 3a. If interests are cen-tered on the firm in an interorganiza-tional network, the network will adoptmisaligned innovations more slowly.This contributes to slower innovationdiffusion rates.

Proposition 3b. If interests extend tothe network in an interorganizationalnetwork, the network will adoptmisaligned innovations more quickly.This contributes to faster innovationdiffusion rates.

Boundary PermeabilityAnother construct that helped toexplain the contrasts between U.S.and Finnish project networks wasboundary permeability. The perme-ability of organizational boundariesplayed a critical role in how projectnetworks adapted to misaligned inno-vations. In the U.S., the boundariesbetween firms in a project networkwere comparatively impermeable. Inthe U.S., adoption of the BuildingModeler innovation required severalfirms to vertically integrate into a sin-gle firm when attempts at redistribut-ing work in the network failed. The 3DCAD applications necessitated suchadaptive responses to changing roles;each of the 3D CAD innovationsrequired the designer to increase his




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or her knowledge of the objects he orshe was designing.

An example of this challenge to tra-ditional network roles was observedoften during data collection whendesigners had to represent the placewhere a wall meets the ceiling. In 2DCAD it sufficed for the architect to sim-ply draw a line where the wall meets theceiling. However, with 3D CAD model-ing, the designer must define the way inwhich the wall object is connected tothe ceiling object. This requiresincreased knowledge of how the struc-ture will be constructed in the field. InU.S. networks, architects generallyrefused to take on this additionalresponsibility because it did not fit witha standard interpretation of their role inthe network. In contrast, Finnish firmsadopting the Home Modeler appli-cation redrew the organizationalboundaries separating the firms in thenetwork without losing their firm iden-tity. The architect took on aspects of thework that had previously been com-pleted by the builder so that the network of firms was quickly ablethrough permeability of organizationalboundaries to garner the benefits of themisaligned innovation.

Researchers are beginning toexplore the role of organizationalboundaries in networks. Jacobides andWinter (2005) investigated integrationand disintegration in Swiss watch mak-ing as a function of organizationalcapabilities. Likewise, Afuah (2001)explored the role of vertical integrationas a response to technological changein the RISC industry. Both of thesestudies explore organizational bound-aries from the perspective of wherethey should be circumscribed and donot address questions of how best torespond to innovations: Should firmsintegrate to eliminate boundaries inthe face of technological change, aswas the case on one of the U.S. net-works we investigated? Or, shouldfirms in the project network remainindependent?

In the cases of the networks weinvestigated, the boundaries in the U.S.networks were impermeable. Becausethey worked with so many differentnetwork partners across projects, firmsin the U.S. found it more difficult tonegotiate changes in their organiza-tional boundaries with other firms toaccommodate the misaligned innova-tion. This contributed to a reduction in the rate of diffusion. Interestingly, inone case, the boundaries separatingfirms in a project network wereremoved when the contractor in thenetwork decided to vertically integratea set of specialist firms from the net-work into its own organization. This ledto tremendous productivity improve-ments as it reduced the impact of theweak relational stability and the firm-level accrual of interests. However, it didnot positively influence the diffusionoutcome because not many others inthe industry followed the same strategyof integration. In the case of the Finnishproject networks, the organizationalboundary was permeable, enabling thedistribution of work to ebb and flow.Firms in the coordinated market econo-my in which Finnish networks form andoperate were able to reallocate workacross organizational boundaries as nec-essary to accommodate the misalignedinnovations. This dynamic capabilitymitigated the impact of the misalign-ment of an innovation on its rate ofdiffusion. These findings enable the for-mulation of the following propositions:

Proposition 4a. If the organizationalboundary between firms in a project net-work is impermeable and work redistrib-ution is impeded, the networks will havesignificant difficulty adapting to mis-aligned innovations. This contributes toslower innovation diffusion rates.

Proposition 4b. If the organization-al boundary between firms in a projectnetwork is permeable and work redistri-bution is enabled, the networks willhave less difficulty adapting to mis-

aligned innovations. This contributes tofaster innovation diffusion rates.

Agent for Project Network ChangeA final construct identified in the com-parison of Finnish and U.S. projectnetworks was the presence of an agentfor project network change. In the liber-al market economy context of the U.S.,firm networks must be self-organizingin the face of pressures for network-level change. The knowledge of aninnovation among firms in the networkcan be distributed unevenly acrossmultiple firms in networks. Moreover,discussions among groups of firms toassess needed changes can easily con-travene tough U.S. antitrust laws andbe viewed internally or externally asillegal collusion. Thus, rational self-organization among firms in the U.S.project networks may not lead to themost rational solution for the entirenetwork. Van de Ven (1986) argued thatin such instances, impeccable micro-logic can lead to macro-nonsense.

In Finland, TEKES, the national tech-nology funding agency, promotes projectnetwork–level productivity enhancingchanges by organizing firms into partner-ship networks to adopt innovations itregards as promising and by directly sub-sidizing the costs such a change mayhave on individual firms in the network.It subsidizes these costs by funding theapplied research on issues associatedwith early adoption of the innovations. Inso doing, the national technology fund-ing agency fulfills the role of an agent forproject network change. Conversely, inthe U.S., this role is inhibited by the liber-al market nature of the economic and insome cases by legal requirements. Thesefindings enable the formulation of thefollowing propositions:

Proposition 5a. In the absence of anagent for project network change, firmsin project networks will have difficultyself-organizing to adopt misalignedinnovations. This contributes to slowerinnovation diffusion rates.

Proposition 5b. In the presence of anagent for project network change, firmsin project networks will benefit fromorchestrated change. This contributes tofaster innovation diffusion rates.

Two-Stage Model for Innovationin Project NetworksIn Table 1, we summarize the con-structs identified in the comparison ofU.S. and Finnish project networks andtheir related dimensions. The tableincludes both the alignment constructand the four constructs relating to proj-ect network dynamics in situations ofinnovation misalignment (relationalstability, interests, boundary permeabil-ity, and agent for project networkchange). Taken together, this set of constructs and related propositionsprovide the foundation for a new theo-retical framework for understandinginnovations being implemented by anddiffusing through networks of firms.

Network StructureBefore we can understand the impactand outcomes of technological inno-vation on a network or a population ofnetworks, we must understand thepreexisting network structure. Onekey aspect of the network structureidentified in this paper is the alloca-tion of work to specialists in the net-work. Because firms in the networkmust work together to complete someoverarching task (e.g., the design and

construction of a building, the pro-duction and distribution of a motionpicture, or the testing and develop-ment of a new drug) certain task inter-dependencies exist that structure theflow of work between firms in the net-work (Thompson, 1967). Sharma andYetton (2003) demonstrated the impor-tance of understanding these taskinterdependencies in relation to thesuccessful implementation of informa-tion systems. The current technologyused by firms in the network is also animportant element of the networkstructure.

In this paper, we illustrate how theallocation of work can vary across mar-kets. However, one would expect allo-cations of work to vary within somemarkets, in particular as innovationsspread from one industry segment toanother. When an innovation is intro-duced into the network, the alignmentof that innovation to the allocation ofwork in the current network structuremust be ascertained before the net-work dynamics can be predicted.Alignment then becomes the moder-ating construct of the first stage of a model for innovation in project networks (see Figure 2). Innovationsthat align with the allocation of workwill circumvent the difficulties associ-ated with implementing innovationsacross project networks. These alignedinnovations can be understood in thecontext of current theoretical frame-

works of organizational innovation(Rogers, 1962). However, innovationsmisaligned with the allocation of workin the network will undergo a dynamicimplementation process unique toproject networks. These innovationsdo not fall within the confines of exist-ing innovation theory.

Project Network Dynamics andDiffusion OutcomesInnovations that are misaligned withthe allocation of work in the networkwill require multiple, interdependenttypes of specialist firms to mutuallyadapt to changes introduced by theinnovation. Therefore, there is a set offirm effects that can be explained byexisting innovation theory as in the caseof aligned innovations. However, in the case of misaligned innovations,more than one type of specialist firmpopulation must adapt to the change.This impacts the rate at which the net-work can adapt to the change. Networkdynamics caused by the inter-firmeffects, however, have a far greaterimpact on diffusion outcomes. Theinter-firm effects invoke a second set ofmoderating constructs (see Figure 2).The degree to which diffusion outcomesare impacted by innovation misalign-ment is determined in this second stageof our grounded theoretical model forinnovation in project networks. The val-ues for the four moderating constructdimensions determine the degree to

Country in Which Project Network Exists

Construct United States Finland

Alignment Derives from allocation of work Derives from allocation of workin the United States in Finland

Relational stability Weak (tendency to contract from Strong (tendency to contract 5-6 firms per specialist type) from 1-3 firms per specialist type)

Interests Firm Network

Boundary permeability Impermeable Permeable

Agent for project network change None (network is self-organizing) National Technology Funding Agencies

Table 1: Comparing project networks in Finland and the United States.




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which misalignment effects are mitigat-ed or exacerbated. Strong relationalstability, network-level interests, perme-able boundaries, and the existence of anagent for project network change willmitigate the impact of misalignment ondiffusion. Conversely, weak relationalstability, firm-level interests, imperme-able boundaries, and the absence of anagent for project network change willexacerbate the impact of misalignmenton diffusion.

Discussion and ImplicationsThe findings from the implementationand diffusion of three innovations in 3D CAD demonstrate that an align-

ment of innovations to project networksgreatly increases the rate of marketacceptance. Data from project net-works in Finland and the U.S. illustratethat in cases of misalignment of inno-vations with the allocation of work innetworks, stronger relational stabilityin the network can mitigate the impactof misalignment on diffusion. In addi-tion, we find evidence that permeableboundaries between firms, network-level accrual of firm interests and thepresence of an agent for project networkchange can all serve to mitigate theeffects of misaligned innovations diffus-ing through project networks. These con-structs and a set of related propositions

have been developed in this paper tobuild a grounded two-stage theoreticalmodel for innovation in project net-works. This research, therefore, con-tributes to a fuller understanding ofinnovation by extending previous orga-nizational innovation theories toinclude innovation in project networks.

Because our model incorporateshow one network can be more success-ful with innovation than another, itaddresses the current tension in theinterorganizational network literatureabout the impact of project networkorganizational structures on innova-tion. Some authors have argued thatproject networks promote innovation

WorkAllocation

CurrentTechnology

MarketShare

MarketAcceptance

Pre-Condition Implementation Process Outcome

Project Network Dynamics

Stage 1Moderating Construct

Alignment Relational StabilityInterests

Boundary PermeabilityAgent for Project Network Change

NewTechnology

NetworkStructure

Diffusion

Interdependence

Stage 2Moderating Constructs

InnovationAligned toNetwork

InnovationMisaligned toNetwork

Intra-Firm Effects(Specialist Type A)

Inter-Firm Effects (A-B)

Intra-Firm Effects(Specialist Type B)

Intra-Firm Effects(Specialist Type A)

Firm Dynamics

Figure 2: Two-stage model for innovation in project networks.

(Ahuja, 2000; Powell, 1998; Powell et al.,1996), while others find project net-works to stifle innovation (Gann &Salter, 2000; Lampel & Shamsie, 2003;Taylor & Levitt, 2004). Networks adopt-ing an innovation that aligns to the allo-cation of work—or that exhibit strongrelational stability, network-level inter-ests, permeable boundaries, and theexistence of an agent for project networkchange when faced with a misalignedinnovation—will perform comparative-ly better than other networks. In thestudies by Powell and his colleagues(1996, 1998), which viewed networks asa locus for innovation, they describedbiotechnology networks as developingtight, knowledge sharing partnerships(strong relational stability) and dis-cussed the important role of theNational Institutes of Health (agent forproject network change). Also becausethe interdependencies were moreresource than task based, allocations ofwork would play a diminished role indetermining innovation outcomes. Ourtwo-stage model for innovation in proj-ect networks would predict that thesebiotechnology project networks wouldbe successful innovators.

In contrast, the motion pictureindustry networks investigated byLampel and Shamsie (2003) exhibitedno clear agent for project networkchange. The move away from studiosorchestrating projects suggests a lack ofan agent for project network change inpost-studio Hollywood. It is also sug-gestive that former teams employed bythe studio would be less focused on thestudio’s interests and more concernedabout their own. Our model would pre-dict that these motion picture industrynetworks would experience some diffi-culty with innovation. Therefore, ourmodel can simultaneously accommo-date the “locus of innovation” findingsof Powell and his colleagues (1996,1998) and the network “stagnation”findings of Lampel and Shamsie (2003).This model then provides a first steptoward resolving divergent views oninnovation in project networks and

strategic guidance for project net-works contemplating adopting newinnovations.

This research contains limitationsthat should be addressed in futureresearch on the subject of innovationin networks. We attempted to accessprecise time-series diffusion data forthe different 3D CAD software applica-tions included in this study. However,we were unable to gain access to suchdetailed quantitative diffusion dataand, necessarily, had to rely on vendor-supplied market data points. In thispaper we describe each of the inducedconstructs in detail; however, the qual-itative nature of our analyses makes itdifficult to unbundle and discern therelative impact of each construct onthe diffusion of misaligned innova-tions. Further research should be con-ducted to determine the contributionof each of the constructs in our modelon diffusion.

This research is also limited in thescope of its data collection. We focusedour data collection on three innova-tions in 3D CAD. Although we are con-fident the theoretical model can assistin predicting the difficulties any mis-aligned innovation may have diffusingthrough project networks, it is impor-tant that this model be tested withother innovations in either replicatedresearch investigations or quantitativehypothesis testing of the propositionsput forward in this paper. A furtherlimitation resulting from a narrowfocus on 3D CAD innovations is thefact that owner organizations in ourdata set do not appear to be playing astrong role advocating for this technol-ogy. Owners have played more figuralroles in the adoption of other innova-tions (e.g., safety-related process inno-vations). Researchers attempting toextend the research in this papershould pay careful attention to the roleof the owner in possibly promoting theinnovation among the project net-works it engages.

Several project networks in the U.S.overcame the impact of high relational

stability through strategies of verticalintegration. A promising direction forfuture research would be to investigatewhether organizational contingencytheory could be extended to apply toproject networks. This could usefully beexplored through both qualitative andquantitative studies. Such a researcheffort would observe the change inorganization boundaries of the net-work in the face of technologicalchange. Though Afuah (2001) hasopened a line of inquiry in this area inthe context of buyer-supplier relation-ships, a fuller understanding of the roleof organizational boundaries wouldencompass situations of reciprocal taskinterdependence.

This research has important impli-cations for firms operating in projectnetworks, particularly those firmsexperiencing difficulty with innovation.The theoretical model presented in thispaper suggests that project networkscontemplating the adoption of techno-logical innovations into their networksshould first understand the alignment ofthat innovation to the allocation ofwork in their network. If the innovationbeing implemented in the network ismisaligned with the current allocationof work, firms in project networksshould strengthen relational stability,realize shared interests, enable thepermeable redistribution of work across organizational boundaries, and work with an agent for project networkchange if one exists. Addressing these factors will enable project net-works to more seamlessly implement technological innovations and morequickly realize concomitant productiv-ity improvements. �

ReferencesAfuah, A. (2001). Dynamic boundariesof the firm: Are firms better off beingvertically integrated in the face of tech-nological change? Academy ofManagement Journal, 44(6),1211–1228.

Ahuja, G. (2000). Collaboration networks, structural holes, and




AP

ER

SP

AP

ER

S

innovation: A longitudinal study.Administrative Science Quarterly,45(3), 425–455.

Barley, S., Freeman, J., & Hybels, R.(1992). Strategic alliances in commer-cial biotechnology. In R. Eccles & N.Norhia (Eds.), Networks and organiza-tions (pp. 311–347). Boston: HarvardBusiness School Press.

Borgatti, S., & Foster, P. (2003). The net-work paradigm in organizationalresearch: A review and typology.Journal of Management, 29(6),991–1013.

Eccles, R. (1981). The quasifirm in theconstruction industry. Journal ofEconomic Behavior and Organization,2(4), 335–357.

Eisenhardt, K. M. (1989). Building the-ories from case study research.Academy of Management Review, 14(4),532–550.

Eisenhardt, K. M. (1991). Better storiesand better constructs: The case forrigor and comparative logic. Academyof Management Review, 16(3), 620–627.

Gann, D., & Salter, A. (2000).Innovation in project-based, service-enhanced firms: The construction ofcomplex products and systems.Research Policy, 29(7–8), 955–972.

Glaser, B., & Strauss, A. (1967). The dis-covery of grounded theory: Strategies forqualitative research. New York: Aldine.

Granovetter, M. (1985). Economicaction and social structure: The prob-lem of embeddedness. AdministrativeScience Quarterly, 91(3), 481–510.

Granovetter, M. (1992). Problems ofexplanation in economic sociology. InN. Nohria & R. Eccles (Eds.), Networksand organizations: Structure, form, andaction (pp. 25–56). Boston: HarvardBusiness School Press.

Gulati, R. (1995). Social structure andalliance formation patterns: A longitu-dinal analysis. Administrative ScienceQuarterly, 40(4), 619–652.

Hall, P., & Soskice, D. (2001). Varietiesof capitalism: The institutional founda-tions of comparative advantage. NewYork: Oxford University Press.

Hamel, G. (1991). Competition forcompetence and inter-partner learn-ing within international strategic

alliances. Strategic ManagementJournal, 12 (Summer Special Issue),83–103.

Hughes, T. P. (1983). Networks ofpower: Electrification in western socie-ty, 1880–1930. Baltimore, MD: JohnsHopkins University Press.

Jacobides, M., & Winter, S. (2005). Theco-evolution of capabilities and trans-action costs: Explaining the institution-al structure of production. StrategicManagement Journal, 26(5), 395–413.

Kanter, R. (1991). The future ofbureaucracy and hierarchy in organi-zational theory: A report from the field.In P. Bordieu & J. Coleman (Eds.),Social theory for a changing society (pp.63–90). Boulder, CO: Westview.

Lampel, J., & Shamsie, J. (2003).Capabilities in motion: New organiza-tional forms and the reshaping of theHollywood movie industry. Journal ofManagement Studies, 40(8), 2189–2210.

Pekar, P., & Allio, R. (1994). Makingalliances work: Guidelines for success.Long Range Planning, 27(4), 54–65.

Pettigrew, A. M. (1990). Longitudinalfield research on change: Theory andpractice. Organization Science, 1(3),267–292.

Podolny, J., & Page, K. (1998). Networkforms of organization. Annual Reviewof Sociology, 24(1), 57–76.

Powell, W. (1987). Hybrid organization-al arrangements: New form or transi-tional development? CaliforniaManagement Review, 30(1), 67–87.

Powell, W. (1990). Neither market norhierarchy: Network forms of organiza-tion. Research in OrganizationalBehavior, 12(1), 295–336.

Powell, W. (1998). Learning from col-laboration: Knowledge and networksin biotechnology and pharmaceuticalindustries. California ManagementReview, 40(3), 228–240.

Powell, W., Koput, K., & Smith-Doerr,L. (1996). Technological change andthe locus of innovation: Networks oflearning in biotechnology.Administrative Science Quarterly,41(1), 116–145.

Rogers, E. (1962). Diffusion of innova-tions. New York: Free Press.

Sharma, R., & Yetton, P. (2003). Thecontingent effects of managementsupport and task interdependence onsuccessful information systems imple-mentation. MIS Quarterly, 27(4),533–555.

Stinchcombe, A. (1959). Bureaucraticand craft administration of production:A comparative study. AdministrativeScience Quarterly, 4(2), 168–187.

Stinchcombe, A. (1968). Constructingsocial theories. New York: Harcourt,Brace and World.

Taylor, J. (in press). Antecedents ofsuccessful 3D CAD implementation indesign and construction networks.Journal of Construction Engineeringand Management.

Taylor, J., & Levitt, R. (2004).Understanding and managingsystemic innovation in project-basedindustries. In D. Slevin, D. Cleland, & J. Pinto (Eds.), Innovations: Project research 2004 (pp. 83–99). NewtownSquare, PA: Project ManagementInstitute.

Taylor J., Levitt, R., & Villarroel, A.(2006). Simulating learning in interor-ganizational networks: The insidiousrole of task interdependence and rela-tional instability in system-level learn-ing. Paper presented at theComputational Analysis of Social andOrganizational Systems NAACSOSConference 2006.

Thompson, J. (1967). Organizations inaction. New York: McGraw-Hill.

Uzzi, B. (1997). Social structure andcompetition in inter-firm networks:The paradox of embeddedness.Administrative Science Quarterly,42(1), 35–67.

Van de Ven, A. H. (1986). Central prob-lems in the management of innova-tion. Management Science, 32(5),590–607.

Williamson, O. (1975). Markets andhierarchies. New York: MacMillan.

Williamson, O. (1985). The economicinstitutions of capitalism. New York:Free Press.

Yin, R. K. (1989). Case study research,design and methods. Newbury Park,CA: Sage Publications.

John E. Taylor, PhD, is an assistant professor inThe University of Texas at Austin’s School ofEngineering. He received his PhD from StanfordUniversity. His research explores how firms inproject networks adapt to disruptive changessuch as new technology implementation andthe international outsourcing of complex engi-neering services activities. As a FulbrightScholar, Dr. Taylor developed his early interest inproject network dynamics while working withthe United Nations to understand and minimizefraudulent freight traffic across national bor-ders. Dr. Taylor develops computational simula-tion models in his research to explore conceptsderived from his in-depth field research. By

grounding his simulation work in field data, he isable to test, extend and develop new organiza-tional theory for project networks. Dr. Taylor isthe director of the Project Network DynamicsLab at The University of Texas at Austin. He isthe founder of two technology startups servingproject-based industries and has five years ofexperience working as a project manager.

Raymond Levitt, PhD, is professor of civil andenvironmental engineering in Stanford’sConstruction Engineering and ManagementProgram. He serves as Director of Stanford’sCollaboratory for Research on Global Projects, andAcademic Director of the award-winning StanfordAdvanced Project Management executive

education program. Dr. Levitt’s “Virtual DesignTeam” (VDT) research group develops new organi-zation theory and computational models to designorganizations for projects and project-based com-panies. His current research is extending VDT tomodel the effects of national institutional differ-ences on the performance of multinational teamsengaged in global infrastructure projects andmultinational, multi-sectoral post-conflict recon-struction efforts. Dr. Levitt was recipient of ASCE’s2000 Computing in Civil Engineering Award andthe society’s 2006 Peurifoy Research Award. Heco-founded and served as initial trustee of the PMINew England Chapter. He was a co-founder, andhas served as a director of, Design Power, Inc., VitéCorp. and Visual Network Design, Inc.


innovation alignment and project network dynamics: an integrative model for change

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