network structure and innovation: the leveraging of … · for the purposes of this study,...

Strategic Management JournalStrat. Mgmt. J., 28: 585–608 (2007)

Published online 7 March 2007 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/smj.621

Received 29 July 2002; Final revision received 29 December 2006

NETWORK STRUCTURE AND INNOVATION: THELEVERAGING OF A DUAL NETWORK AS ADISTINCTIVE RELATIONAL CAPABILITY

ANTONIO CAPALDO*Catholic University of the Sacred Heart, Milan, Italy

This paper employs comparative longitudinal case study research to investigate why and howstrong dyadic interfirm ties and two alternative network architectures (a ‘strong ties network’and a ‘dual network’) impact the innovative capability of the lead firm in an alliance network. Ianswer these intrinsically cross-level research questions by examining how three design-intensivefurnishings manufacturers managed their networks of joint-design alliances with consultingindustrial design firms over more than 30 years. Initially, in order to explore the sample leadfirms’ alliance behavior, I advance an operationalization of interorganizational tie strength. Next,I unveil the strengths of strong ties and the weaknesses of a strong ties network. Finally, I showthat the ability to integrate a large periphery of heterogeneous weak ties and a core of strong tiesis a distinctive lead firm’s relational capability, one that provides fertile ground for leading firmsin knowledge-intensive alliance networks to gain competitive advantages whose sustainability isprimarily based on the dynamic innovative capability resulting from leveraging a dual networkarchitecture. Copyright 2007 John Wiley & Sons, Ltd.

INTRODUCTION

The growing importance of alliance networksas competitive units (Gimeno, 2004; Nohria andGarcia-Pont, 1991) and the need to develop adeeper appreciation of networks’ dynamics (Brasset al., 2004; Madhavan, Koka, and Prescott, 1998)make it urgent that we expand our understanding ofhow firms that play the role of the ‘strategic center’(Lorenzoni and Baden Fuller, 1995) in interfirmnetworks (i.e., lead firms) manage their web ofpartners over time. Building on previous research,I argue that, to be able to manage their networksstrategically, lead firms require a distinctive set of

Keywords: cross-level research; embeddedness; inter-firm network management; knowledge-intensive strategicalliances; strength of ties; industrial design*Correspondence to: Antonio Capaldo, Department of Manage-ment, Catholic University of the Sacred Heart, 1 Largo Gemelli,Milan 20123, Italy. E-mail: [email protected]

relational capabilities. The primary objective ofthis study is to shed light on a single relationalcapability, namely the lead firm’s capability to sus-tain its innovativeness by creating and managingthe overall architecture of its network over time.This demands a deeper analysis of the relationshipsbetween network structure and firm-level innova-tion.

Despite some research on the relationships bet-ween network structure and effectiveness in healthservices (Provan and Milward, 1995), and betweennetwork structure and various organizational out-comes in SME networks (Human and Provan,1997), little is known about whether, why, and howdifferent network architectures exert asymmetricimpacts on the innovative capability of the net-work’s leading actor. Several contributions (Uzzi,1997; Rowley, Behrens, and Krackhardt, 2000)have yielded valuable advances by drawing on

Copyright 2007 John Wiley & Sons, Ltd.

586 A. Capaldo

(and adding to) social network theory. In partic-ular, the strength of (interorganizational) ties hasbeen employed in cross-level research aimed atanalyzing the structure of interfirm networks andits impact on firm-level innovation (e.g., McEvilyand Zaheer, 1999).

However, the operationalization of interorgani-zational tie strength awaits further contributions.Moreover, at the network level of analysis, andfocusing specifically on the intersection with thefirm level, both the weaknesses of a network archi-tecture in which strong ties predominate (i.e., a‘strong ties network’) and the strengths of a ‘dualnetwork’—that is, a network architecture whereina small core of strong ties is integrated with alarger periphery of weak ties—need to be uncov-ered. This, in turn, takes us back to some criticalquestions at the dyad level of analysis, specificallyat the intersection with the firm level. Here, whilethe strength of weak ties has often been empha-sized, the strength of strong ties and the processesthrough which strong ties support firm-level inno-vation deserve further research.

My purpose in this paper is to attempt to fill theabove gaps by investigating the relational capa-bility of three lead firms to sustain their innova-tion over time by leveraging the structure of theiralliance networks. To this end, I apply compara-tive longitudinal case study research to answer twomajor and strictly linked research questions that cutacross different levels of analysis while sharing thesame firm-level outcome variable, namely the leadfirm’s innovative capability. My research questionsare: ‘Why and how do strong dyadic ties impact thelead firm’s innovative capability over time?’; and‘Why and how do alternative network structures(i.e., a strong ties network and a dual network)impact the lead firm’s innovative capability overtime?’

As a result, I offer the following contribu-tions. First, I advance an operationalization of thestrength of interorganizational relationships thatbuilds on Granovetter’s (1973) original definitionof tie strength. Second, I discuss the strengthsof strong ties, the weaknesses of a strong tiesnetwork, and the processes through which strongties and a strong ties network exert their influ-ence over time on the lead firm’s capability toinnovate. Finally, I explain why and how a dualnetwork architecture impacts positively the inno-vative capability of its leading actor, and I arguethat lead firms can sustain their innovation over

time by relying on dual networks. By doing so,I contribute to our knowledge of the relationalcapabilities that lead firms leverage to build andsustain competitive advantages, in an attempt tooffer valuable insights for academics and practi-tioners alike.

The paper is organized as follows. After review-ing the relevant literature and addressing majorlevels issues and the operationalization of tiestrength, I set out methods and results of a com-parative longitudinal study of how three samplefurnishings manufacturers managed their large net-works of dyadic joint-design alliances over aninvestigation period of more than 30 years. Thefinal sections contain discussion and conclusion,together with limitations, implications for man-agers, and avenues for further research.

THEORETICAL BACKGROUND

Relational capabilities for alliance networkmanagement

For the purposes of this study, alliances1 are inter-firm collaborative relationships directed to the gen-eration of relational rents (Dyer and Singh, 1998).They consist of joint value-creation processes(Zajac and Olsen, 1993) which develop over time(Ring and Van de Ven, 1994) and are embeddedin their surrounding social context (Gulati, 1998).Recent contributions describe alliance networks asstrategic assets (i.e., ‘strategic networks’: Gulati,Nohria, and Zaheer, 2000) that lead firms leverageto generate differential returns for both partici-pating firms and the network as a whole (Baum,Calabrese, and Silverman, 2000; Dyer and Hatch,2006; Gomes-Casseres, 1996). However, networkmanagement requires a deeper understanding of itsinherent challenges (Das and Teng, 2002; Jones,Hesterly, and Borgatti, 1997; Sobrero and Roberts,2001). Specifically, the development and leverag-ing of a distinctive set of relational capabilities iscrucial for the lead firm to be able to tap into thestrategic potential of its alliance web.

The debate on relational capabilities is still inits infancy. In an influential paper, Powell, Koput,

1 I use henceforth the expressions (strategic) alliances and(interorganizational) relationships or ties interchangeably to referto the definition of alliances advanced here. The (interfirm) net-works I refer to in this study are alliance networks.

Copyright 2007 John Wiley & Sons, Ltd. Strat. Mgmt. J., 28: 585–608 (2007)DOI: 10.1002/smj

Dual Networks, Innovation, and Relational Capability 587

and Smith-Doerr (1996) sketched out the organi-zational capability to manage ‘networks of learn-ing’ as consisting of routines specifically devotedto interorganizational knowledge transfer. Morerecently, Dyer and Nobeoka (2000) have examinedin detail the knowledge-sharing routines developedby Toyota to promote superior learning in its sup-plier network. Along a similar vein, Lorenzoni andLipparini (1999) have argued that the ability tointegrate knowledge that resides both inside andoutside a firm’s boundaries is a distinctive capa-bility for transactionally intensive firms. Interest-ingly, these contributions share a knowledge-basedperspective according to which alliance networksare created and managed by lead firms whichleverage network-wide knowledge access, trans-fer, and creation to generate competitive advan-tages based on superior innovation. Building onthese insights, I investigate how three lead firmsshaped the structure of their knowledge-intensivenetworks over time to sustain their innovativecapability.

Innovation, network structure, and strength ofties

The positive impact of interfirm networks oninnovation has been traced back to the poten-tial of interorganizational collaboration to facil-itate knowledge sharing and interactive learningprocesses among participating firms (Inkpen andTsang, 2005; Powell et al., 1996). This potential,in turn, is claimed to be strongly dependent onthe overall network structure (e.g., Ahuja, 2000a;Zaheer and Bell, 2005). Essential to this reason-ing is the notion of ‘bridge’ (Harary, Norman,and Cartwright, 1965). According to Burt’s (1992)principles for network building, a focal firm shouldmaximize the proportion of bridges (i.e., nonre-dundant contacts) to total contacts in the network.This has relevant implications in the case of a leadfirm and its first-order alliance network: in orderto increase its potential to generate innovation, thelead firm should focus on the diversity of its directcontacts, whose number is relevant to the extentthat it increases the probability of network diver-sity.

The above reasoning has considerable connec-tions with strength-of-ties arguments. Tie strengthresearchers typically classify both interpersonaland interorganizational relationships as being eitherstrong or weak. As Granovetter (1973) pointed

out, strong ties (i.e., long-lasting, repeated, andsocially dense relationships) cannot be bridges.Conversely, although weak ties are not automat-ically bridges, bridges tend to be weak ties (seealso Friedkin, 1980), which leads to ‘the strengthof weak ties’ (Granovetter, 1973). In the domainof interorganizational relationships, the strength ofweak ties results from the potential of weak tiesto foster and speed up innovation by connectinga focal firm to otherwise difficult-to-reach knowl-edge areas (Rogers, 2003). By adding weak ties toits network, a lead firm is likely to add nonredun-dant contacts and hence expand network diversity(Burt, 1992), thereby increasing its performance(Rowley et al., 2000).

Other scholars have claimed the strength ofstrong ties (Krackhardt, 1992; Nelson, 1989).Strong interfirm ties are valuable competitive tools,especially for lead firms faced with uncertainty(Keister, 1999). Indeed, they can offer steady flowsof new ideas, technological innovations, and oper-ational support. Several studies in the domain ofinterfirm alliances have highlighted how strong tiesencourage reciprocity, a long-term perspective, andjoint problem-solving arrangements (Larson, 1992;Uzzi, 1997). Also, strong ties have been foundto stimulate knowledge transfer and protection ininterorganizational settings (Dyer and Nobeoka,2000; Kale, Singh, and Perlmutter, 2000) and pro-mote adaptation to environmental changes (Kraatz,1998).

However, the benefits that strong ties bring tothe innovation processes deserve further system-atic research. Moreover, moving upward from thedyad level to the network level of analysis, Uzzi’s(1997) notion of ‘overembeddedness’ suggests thatstrategic networks composed mostly of strong tiesmay threaten innovation, rather than enhancing it.Finally, the distinctive and somewhat complemen-tary roles of weak and strong ties lead to theidea that integrating strong and weak ties withinthe same alliance network would guarantee supe-rior firm-level innovation due to the coexistingopportunities for exploitation and exploration, andwould therefore represent a distinctive relationalcapability for the leading actor in the network. Fol-lowing this route, at the outset of this research Iadvanced the argument that network architecturesthat differ in tie strength exert a different impacton the innovative capability of the lead firm in analliance network.


588 A. Capaldo

LEVELS ISSUES IN NETWORKRESEARCH

The present study adopts a theoretical stanceinformed by social network research. Levels-of-analysis issues are especially relevant for networkresearchers, whose research questions usually lieat the intersection between different levels. For thepurposes of this paper, two such issues are worthaddressing.

First, in social network research ‘micro andmacro can be very similar theoretically and metho-dologically’ (Borgatti and Foster, 2003: 1001), andthus theories and constructs initially developed forthe study of interpersonal relationships are fre-quently applied to the analysis of interorganiza-tional linkages. In addition, network researchersin the field of interfirm relationships have com-monly resorted to dyadic constructs and data toexplore firm-, dyad-, network-, and mixed-levelresearch questions (Borgatti and Foster, 2003).Thus, after its birth and early use in the domainof interpersonal relationships (Granovetter, 1973),the strength of ties has been recently employedas a major (dyad-level) theoretical construct toanalyze interorganizational relationships, in par-ticular the structure of interfirm networks and itsimpact on learning and innovation, often at thelevel of single firms (e.g., McEvily and Zaheer,1999). This has two major implications. First, weneed to tackle the operationalization of tie strengthwith specific reference to the interorganizationallevel—a point I will resume later in this paper.Second, the above tie-strength research in interor-ganizational settings is intrinsically cross-level, asit tries to draw causal models of the relationshipsbetween constructs across different levels of analy-sis (Rousseau, 1985), usually with the aim of deep-ening the understanding of the impact of network-and dyad-level variables on firm-level innovation.This is also the case with the present study, whichacknowledges its cross-level nature and thereforeranges over and across three levels of analysis: thelead firm level, the dyad level, and the networklevel.

A second levels issue in network research con-cerns the linkages between interpersonal and inter-organizational relationships. In fact, since interor-ganizational relationships are managed by indi-vidual boundary spanners who interact on behalfof their organizations across the organizations’boundaries, micro behaviors at the interpersonal

level generate macro outcomes at the interorgani-zational level (e.g., Zaheer, McEvily, and Perrone,1998). Accordingly, I argue that social contentsand trust existing in the relationships between indi-vidual participants in interfirm alliances impactthe relationships between their organizations, andspecifically increase the strength of interorgani-zational relationships.2 Consequently, this paperemphasizes the interpersonal side of interfirmalliances and takes it into account in operational-izing tie strength at the interorganizational level.

OPERATIONALIZING TIE STRENGTH

The strength of ties is a primary construct in inves-tigating this study’s research questions. At first,Granovetter (1973: 1361) framed tie strength atthe interpersonal level of analysis as a continu-ous (dependent) variable resulting from a linearcombination of a set of (independent) variablesexpressing multiple dimensions of partners’ behav-ior in the relationship. Along a continuum of tiestrength, the definition advanced by Granovetterwould allow us to distinguish between strong(er)and weak(er) ties on the basis of how partnersbehave in the relationships. Since then, the strengthof ties has been employed extensively to analyzesocial structure and action at both interpersonaland interorganizational levels (Granovetter, 1982;Rogers, 2003), while little effort has been madeto distinguish between interpersonal and interorga-nizational tie strength. From a substantive stand-point, extant strength-of-ties literature on both lev-els provide considerable evidence that partnersinvolved in dyads holding the same kind of rela-tionship (strong or weak) behave homogeneously.Conversely, the behavior of partners in strong tieshas been found to be different from that of partnersin weak ties.

From a methodological perspective, the richnessof Granovetter’s original proposal has largely beenneglected. To begin with, in his classic study,Granovetter (1974) himself operationalized stronginterpersonal ties as those who interacted at leasttwice per week. Analogously, the frequency ofinteraction has been adopted in subsequent works

2 This linkage also operates the other way round. Indeed, interor-ganizational relationships imbued with trust and reciprocity willinduce and/or strengthen social contents among participatingindividuals, thereby increasing the strength of interpersonal rela-tionships between individual boundary spanners.



as a proxy for the strength of interorganizationalas well as interpersonal relationships (McEvily andZaheer, 1999; Nelson, 1989), with the cut-off valuebeing modified according to the nature and contentof the relationships. However, a single variablemay not fully capture all the relevant dimensionsof partners’ behavior, and any cut-off value set toseparate strong from weak ties may in fact easilyturn out to be arbitrary.

Further, in his study of strong interpersonal ties,Krackhardt (1992) criticized the definition of tiestrength as a continuous variable, which wouldgenerate ambiguity as to the strength of each singlerelationship. Thus, Rowley et al. (2000) conceptu-alize strong and weak interorganizational ties asseparate constructs, different in kind rather thandegree. They categorize equity alliances, joint ven-tures, and nonequity cooperative (R&D) venturesas strong ties, while defining marketing agree-ments, and licensing and patent agreements asweak ties, thereby capturing the strength of inter-firm relationships on the basis of the partners’typical levels of interaction in, and resource com-mitment to, each alliance type. While offering use-ful insights, this approach is prone to limitations.First, it underestimates the social dimension of theexchange, which the authors deem to be pertinentfor individual-level relationships, but not as appli-cable to interfirm alliances. Second, whereas it maybe useful to separate strong from weak ties ina sample including strategic alliances of differenttypes, the operationalization proposed by Rowleyand colleagues is of little help for measuring therelative strength of interfirm ties of a single type,as is the case with the research presented here.Finally, by considering typical levels of interactionand resource commitment, rather than exploringdirectly how partners behave, and by focusing ona small number of alliance types, rather than oneach single alliance, the authors draw an a prioridistinction that is unlikely to fit the wide variety ofinterorganizational relationships and their dynam-ics.

To overcome the shortcomings of previousresearch, I offer an operationalization of thestrength of interorganizational ties that capitalizeson Granovetter’s (1973) original proposal. I there-fore conceptualize strong and weak ties as degreesof one another, and I separate clusters of strong andweak ties not by fixing a cut-off value, but insteadon the basis of their internal homogeneity andexternal heterogeneity, which result from a direct

investigation of multiple dimensions of partners’behavior in each single relationship. By doing so,I also build on previous strength-of-ties research atthe interorganizational level of analysis, whereinthree major aspects of partnering behavior havebeen advanced to express tie strength: the amountof time that characterizes the tie (Kraatz, 1998), thepartners’ level of resource commitment (Rowleyet al., 2000), and the social contents which developat both interpersonal and interorganizational levels(Rindfleisch and Moorman, 2001).

Coherently, I frame tie strength as a three-dimensional concept composed of a temporal di-mension, a resource dimension, and a social dimen-sion. Thus, strong(er) interfirm ties are character-ized by long(er) time-frames and high(er) resourcecommitments when compared to weak(er) ties, aswell as by tight(er) interpersonal relations andtrust-based interorganizational linkages. I arguethat the following three variables should be em-ployed to express the strength of an interorgani-zational relationship: (1) the relationship’s overallduration; (2) the frequency of collaboration; and(3) the intensity of collaboration. The higher therelationship’s duration, and the higher the fre-quency and intensity of collaboration, the higherthe strength of the relationship.

Taken together, duration, frequency, and inten-sity express the above three dimensions of tiestrength. The last two variables measure interac-tion between partners—the higher the frequencyand intensity of collaboration, the more the inter-action. They express separate, but equally relevant,aspects of the temporal dimension of tie strength,and therefore they need to be jointly taken intoaccount. Consider tie A and tie B, having the samefrequency of collaboration: if partners in tie A col-laborate more (less) intensely than those in tie B,then they devote more (less) time to the relation-ship, and hence are involved in a stronger (weaker)tie. Duration completes the assessment of the tem-poral dimension of tie strength. In fact, for anygiven level of frequency and intensity of collabo-ration, the longer (shorter) the relationship’s dura-tion, the higher (lower) the overall amount of timespent by partners in the relationship, and hence thestronger (weaker) the tie.

Duration, frequency and intensity also synthe-size the resource dimension and the social dimen-sion of tie strength. On the one hand, otherthings being equal, long-lived, frequent and intenseinterorganizational relationships entail higher


590 A. Capaldo

resource commitments than short-lived partner-ships characterized by low levels of interaction.On the other hand, in some degree, frequency andintensity of collaboration are necessary (althoughnot sufficient) conditions for the social dimensionto develop in interfirm partnerships. As interac-tion increases, interpersonal relations are strength-ened and the mutual awareness that provides thefoundation for (knowledge-based) interorganiza-tional trust is deepened, thereby also encouragingpartners to make higher resource commitments tothe relationship. This, in turn, stimulates mutual(deterrence-based) trust, while reciprocity becomesan unwritten rule. Moreover, a long relationship’soverall duration allows the above social contentsto accumulate and reinforce over time, therebystrengthening the tie. Conversely, the lower therelationship’s duration, and the frequency andintensity of collaboration, the thinner the socialdimension tends to be, and hence the weakerthe tie.

RESEARCH DESIGN

My intent of filling relevant gaps in the extantliterature on strategic networks and exploring therising field of relational capabilities led me to con-duct an inductive study. I carried out compara-tive longitudinal multiple-level case study researchwith the aim of developing theory from an in-depth examination of three lead firms and thedynamics of their alliance networks. FollowingYin (1994), the case study was deemed an appro-priate research strategy to help understand thephenomena under investigation within their rich(inter)organizational contexts by relying on sev-eral sources of evidence, while the multiple-casecomparative approach guaranteed the robustnessof the findings (Pettigrew, 1997). The longitudi-nal structure of the cases, based on a retrospec-tive multiple time-period design, allowed me tomeasure the innovative performance of each leadfirm in subsequent time periods and to observe thenetwork structure leveraged by each company ineach period, while also providing multiple obser-vations of the processes through which both singleties and the overall networks affected innovation.The multiple-level structure of the cases produceda study ranging over and across three levels ofanalysis—the lead firm level, the dyad level, andthe network level—in a way that allowed me to

investigate my cross-level research questions thor-oughly.

Consistent with a multiple-case research strat-egy, the study incorporated a replication (ratherthan a sampling) logic, in which multiple cases aretreated as analogous to multiple experiments ableto confirm, disconfirm, or refine emerging relation-ships between significant constructs in an itera-tive process of theory building (Eisenhardt, 1989;Yin, 1994). In addition, the investigation of mul-tiple time periods in each case, together with bothwithin-case comparisons across subsequent periodsand cross-case comparisons, sustained the internaland the external validity of the study.

After an initial groundwork phase, during whichI developed my research questions and designand selected the research setting, sample and datasources, I followed a two-stage research process.Stage one integrated quantitative and qualitativedata to unravel the linkage between two archetypi-cal network architectures, emerging from the longi-tudinal analysis of the sample lead firms’ alliancebehavior, and the lead firms’ innovative perfor-mance. Stage two relied on the convergence ofqualitative information from different sources toadvance an explanation of the evidence gathered inthe previous stage cutting across the three selectedlevels of analysis.

Research setting

The research setting is the Italian furnishingsindustry, which includes the production of fur-niture, lighting, and complements of furnishings.Here, a number of manufacturers are major inter-national players, whose success is largely depen-dent on their ability to leverage industrial design asa primary source of continuous product innovation.Instead of relying exclusively on internal designdepartments, these companies are used to draw-ing new product ideas and specialized technicalskills from networks of dyadic alliances with con-sulting industrial design firms (design firms, here-inafter), which in turn collaborate simultaneouslywith manufacturers operating in different indus-tries. This leads to an intricate pattern of inter-connected networks that increases the creativity ofexternal designers, by broadening their exposure toknowledge flows, and offers manufacturers a widerspectrum (both in terms of quantity and variety) ofstimuli on the aesthetic, functional, and technicalsides of innovation. While such a complex web of



relationships is difficult to disentangle, governingthe first-order network of design firms has a pri-mary, yet poorly understood, role in the overallstrategic management of several Italian design-intensive furnishings manufacturers.

Design firms are usually small (employing notmore than five or six individuals), European (oftenItalian), and highly specialized in industrial design.These firms pivot on their promoting partners,well-known industrial designers (or architects)whose creativity, technical know-how, long-livedrelationships with manufacturers, and personal rep-utations are a major part of the organization’s assetbase. Following my informants’ usage, I describedesign firms as ‘external designers’ and I nameeach firm using the surname(s) of its promotingpartner(s).

Sample

During the groundwork phase, I interviewed theCEOs and managers of numerous firms, and sev-eral industrial designers and industrial designscholars. These exploratory interviews were pri-marily aimed at selecting a small number ofleading design-intensive furnishings manufacturerswhose strategy hinged upon a network of allianceswith design firms. Industry reports, evaluatingfinancial performances and competitive strategiesof the leading Italian furnishings manufacturers(Databank, 1997a, 1997b, 1997c), and a question-naire, aimed at collecting data concerning howthey manage innovation, were also employed. As aresult, three lead firms—which had described theleveraging of their network of design firms as ‘veryimportant’ to their adaptiveness, innovation, and

overall performance—were identified for in-depthstudy.

After originating in the genius of one or a fewindividuals for design and innovation, the threesample lead firms developed from the efforts ofseveral members of their founders’ families, andthus the histories of these companies are deeplyintertwined with the vicissitudes of those fami-lies. Over the last four decades, these organiza-tions have played a primary role in the historyof industrial design worldwide by joint-designingwith world-famous external designers, and launch-ing onto the market, ‘cult products’ that haveshaped the imagery and taste of several genera-tions. Table 1 provides an outline of the sampleand some basic information on the three lead firms’alliance activity during the investigation period.

Data

The collection of data lasted from September 1998to October 2000, with an additional wave fromMarch 2003 to October 2003. I employed multi-ple data collection methods to exploit the syner-gistic effects of combining them via triangulation(Jick, 1979). Five main sources of evidence wereselected.

Archival records

After extensive historical reconstruction, the com-panies’ archives yielded detailed information aboutthe three lead firms’ innovative performance andthe strength of their alliances with external design-ers over the investigation period.

Table 1. Sample firms outline

Lead firms Business areas Workforce(no. of

employees)a

Net sales($ mill.)a

Exportson net

sales (%)a

Investigationperiod

Alliance activity duringinvestigation period

B&B Italia Furniture andcomplements

501 124.5 69.4 1966–2000 152 joint-design agreementswith 30 design firms

Cassina Furniture andcomplements


iGuzzini Indoor and outdoorlighting


a Workforce, net sales, and exports on net sales refer to 2002.


592 A. Capaldo

Retrospective individual interviews

I interviewed the CEOs and several long-standingtop managers of the sample lead firms, as wellas a number of external designers who had col-laborated with the three firms over the investi-gation period. Interviews were tape-recorded andtranscribed. In total, nearly 46 hours of interviewswere conducted with 18 individual respondents.

Focused individual interviews

I interviewed the directors of the three lead firms’organizational units (i.e., R&D; Design; Market-ing and Sales) directly involved in collaborativeactivities with external designers. Interviews weretape-recorded and transcribed. Follow-up ques-tions were explored through a combination of face-to-face interviews and telephone conversations.In total, nearly 48 hours of interviews were con-ducted with 12 individual respondents.

Direct observation

I was able to directly observe events and actors’behaviors throughout numerous field visits. Attwo study sites I was also allowed to attend‘design reviews’—that is, periodic meetings dur-ing which external designers, top managers, tech-nicians, and internal designers discussed new prod-ucts at subsequent stages of their development pro-cesses.

Documentary information

I gathered several materials produced by and aboutthe sample firms, including CD-ROMs, catalogs,and minutes of meetings with external design-ers. Previous studies, research reports, and booksedited by the companies themselves helped thereconstruction of the three lead firms’ history. Fur-ther information was gathered from the Internet,business press articles, and industrial design jour-nals.

STAGE ONE

In stage one, I defined the outcome variable of thestudy as the lead firm’s innovative capability. Fol-lowing previous studies (e.g., Ahuja, 2000b), in the

empirical research I employed the lead firm’s inno-vative performance as a proxy for the firm’s capa-bility to innovate. I focused specifically on productinnovation performance. Initially, I relied on theinterviewees to evaluate how such performancehad evolved over time in my three cases. Overall,my interviews generated a picture of three suc-cessful companies, whose normally above-averageinnovativeness had slowed down, however, duringmultiple-year time periods which I labeled ‘opaquephases.’ Documentary information and two indus-try experts corroborated these early findings, andin particular confirmed that the opaque phases hadrepresented a standstill, rather than a collapse, inthe firms’ innovative performance.

In search of additional quantitative evidence,following my informants’ suggestions I consid-ered both ‘inside’ and ‘outside’ perspectives on theinnovative performance of design-intensive fur-nishings manufacturers. This led me to select threeindicators.

As far as the inside perspective is concerned, Ideemed a firm’s product innovation output, mea-sured as the number of new products launchedonto the market, a first appropriate indicator. Fromthe outside perspective, I first considered mar-ket feedback to be especially relevant to expressinnovation for manufacturers targeting demand-ing, innovation-oriented customer groups. Giventhat, in the sample organizations, product portfo-lio decisions are largely market-driven, includingdecisions about which products should be with-drawn from the market and when, I captured mar-ket feedback for each new product by the numberof years between the launch of the product andits withdrawal from the market (i.e., new productduration). Further, following previous studies (e.g.,Miller and Shamsie, 1996), I employed the critics’ratings as a third indicator of creativity and inno-vation. Analogously to what Rao (1994) has foundin the automobile industry, success in contests thatreward product innovation indeed plays a primaryrole in the legitimation process for design-intensivemanufacturers by helping to establish and reinforceover time a favorable organizational reputation forinnovation (see also Gemser and Wijnberg, 2002).I measured the critics’ ratings as the number ofprize-winning and commended new products invarious major innovation-focused contests previ-ously selected by two industry experts.

In each case, my three indicators confirmed thatthe lead firms’ innovative performance had been



systematically lower during the opaque phases andhigher during the remaining time periods, which Itherefore labeled ‘brilliant phases.’

Next, in order to explore a basic idea of myresearch—that is, both the strength of dyadicalliances and the architecture of the overall net-work exert a relevant impact on the lead firm’sinnovative capability—I analyzed longitudinallyhow the structure of the three networks basedaround the sample lead firms had evolved overtime across the brilliant and opaque phases. Asdiscussed earlier, I operationalized the strength ofeach single manufacturer–design firm alliance asa linear combination of the following variables:the relationship’s overall duration, measured asthe overall time-span (expressed in years) betweenthe subscription of the first joint-design agree-ment and the launch of the last joint-designednew product; the frequency of collaboration, mea-sured as the number of individual years in whichthe manufacturer and the design firm had actuallycollaborated on joint activities during the relation-ship’s overall duration; and the intensity of collab-oration, measured as the number of joint-designagreements signed during the relationship’s overallduration.

For each case, archival records allowed me tocreate a relational database containing informationon the overall duration, and on the frequency andintensity of collaboration, of every dyadic joint-design alliance held by the lead firm during eachsingle phase. As the three lead firms did not filehard data about ‘failures’ (i.e., agreements thathad not yielded finished products), I included onlyformal agreements that had resulted in at leastone finished product. I then calculated standard-ized measurements to remove the scale effect. Iemployed the mean absolute deviation for datastandardization. Following Hampel et al. (1986),I deemed it a more robust (i.e., less sensitiveto outlying values) dispersion measure than thestandard deviation. For each historical phase, thisallowed me to obtain a standardized data matrix,which I analyzed through the following analyticalsteps.

First, I used principal component analysis (PCA)to reduce the number of initial variables by con-structing new, uncorrelated variables (i.e., princi-pal components) that are linear combines of theinitial ones and retain decreasing percentages oftotal inertia from the original data (Bouroche andSaporta, 1983; Jolliffe, 1986). For each lead firm

and every historical phase, PCA results revealed asplit in the network between a ‘core’ of strong(er)ties and a ‘periphery’ of weak(er) ties. Second,I turned to cluster analysis (CA) to design theboundaries between core and periphery, therebyascertaining their size and composition (Everitt,1974). I employed two CA techniques—a non-hierarchical technique based on MacQueen’s(1967) k-means method and an ascendant hierar-chical technique (Ward, 1963)—in order to cross-check their results (Bouroche and Saporta, 1983).Finally, I compared the results of the two previousanalytical steps across the phases, so as to shedlight on the dynamics of the network structure ineach case.

Alternative network structures and lead firminnovation

Table 2 shows the brilliant (white rows) and theopaque (shaded rows) phases that emerged fromthe longitudinal analysis of the sample lead firms’innovative performance, together with representa-tive excerpts from the interviews. Note that thecut-off years between the phases were set on thebasis of my retrospective interviews and conversa-tions with two industry experts. In sum, while thehistory of B&B Italia and the history of iGuzzinishow two short opaque phases interrupting threelonger brilliant phases, for Cassina a single 8-year opaque phase divides two longer brilliantphases.

For each case and every phase, my analysisof the relational databases yielded significant andstrong correlations among the three initial vari-ables. Therefore, the PCA results summarized inTable 33 show that the first principal component(PC1) always accounts for a high percentage oftotal inertia (between 90.16% and 99.16%). More-over, PC1 is always strongly and positively corre-lated with the initial variables (≥0.90). Thus, thecoordinates of the design firms on PC1 faithfullyexpress tie strength: the higher the coordinate, thestronger the corresponding tie. Those coordinatesare employed in Figure 1 to produce graphical dis-plays of the networks in which lines representalliances, and the distance of each design firm (i.e.,each dot) from the lead firm (i.e., the empty circleat the center of each network)—or, in other words,the length of each line—is inversely proportional

3 Full PCA results are available from the author upon request.


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Table 3. B&B Italia, Cassina, and iGuzzini: summary of PCA results

Lead firms Phases First principal component (PC1) Correlations between PC1 andinitial variables

Eigenvalue % of total inertia Duration Frequency Intensity

B&B Italia Phase 1 2.97 99.07 0.99 1.00 0.99Phase 2 2.96 98.70 0.99 0.99 1.00Phase 3 2.79 93.12 0.91 0.95 0.98Phase 4 2.98 99.16 0.99 1.00 1.00Phase 5 2.72 90.68 0.96 0.97 0.91

Cassina Phase 1 2.71 90.16 0.97 0.98 0.90Phase 2 2.77 92.21 0.97 0.96 0.95Phase 3 2.71 90.21 0.96 0.96 0.93

iGuzzini Phase 1 2.72 90.70 0.97 0.97 0.92Phase 2 2.88 96.10 0.99 0.99 0.97Phase 3 2.81 93.66 0.97 0.99 0.95Phase 4 2.97 98.95 0.99 1.00 0.99Phase 5 2.74 91.37 0.98 0.97 0.91

Table 4. B&B Italia, Cassina, and iGuzzini: network structure in brilliant and opaque phases

to the strength of the relationship between them:the longer the distance, the weaker the tie. Notethat, since the coordinates of the design firms onPC1 allowed me to calculate the distances betweenevery pair of the n design firms, rather than thedistances of each individual design firm (df) fromthe lead firm, for each phase I set the distancebetween the strongest contact (df1) and the leadfirm (lf) equal to 1 (Ddf1 – lf = 1), so as to calculate

the distances of the remaining i contacts from thelead firm (Ddfi – lf; i = 2, 3, . . . , n) as follows:

Ddfi – lf = Ddf1 – lf + Ddfi – df1 = 1 + Ddfi – df1

The graduated axis on the northwest side of eachdisplay helps the reader evaluate and compare theabove distances, and hence the strength of the cor-responding ties. Figure 1 shows the core of strong


596 A. Capaldo

contacts (underlined and closer to the lead firm)and the periphery of weak contacts (farther fromthe lead firm) for each of the three firms in everyphase. However, quite different proportions ofstrong and weak ties can be observed between thebrilliant (white areas) and opaque (shaded areas)phases. For each phase the two CA techniquesyielded identical results for membership of the net-works’ core and periphery, which are shown inFigure 1 separated by dotted circles.

Although strong and weak ties coexist in everyphase, Figure 1 suggests two different archetypi-cal network structures, whose distinctive featuresemerge from data reported in Table 4. In theopaque phases (shaded rows), the network core ofstrong ties appears to cover a large proportion oftotal membership in the network (between 66.7%and 75%) and to account for the preponderantshare of the lead firm’s overall alliance activ-ity in terms of relationships’ duration (between76.5% and 88%) and of frequency (between 80%and 88.5%) and intensity (between 85.7% and92.3%) of collaboration with external designers.Conversely, weak ties play a marginal role. Hence,the alliance web can be said to show a strong tiesnetwork architecture.

On the contrary, in the brilliant phases (whiterows), weak ties prevail over strong ties in numer-ical terms, holding the major proportion of totalmembership in the network (between 72.7% and84.6%). When compared to the opaque phases,the network periphery of weak ties accounts for aquite larger share of the lead firm’s overall allianceactivity in terms of relationship duration (between51.7% and 67.9%) and of frequency (between55.4% and 67.9%) and intensity (between 33.3%and 48.6%) of collaboration with external design-ers. However, as strong ties also play a signifi-cant role by absorbing a considerable share of thelead firm’s overall alliance activity, in the brilliantphases the alliance web displays what I label a dualnetwork architecture.

In summary, during stage one, my analysis ofthe dynamics of the innovative performance of thethree lead firms and the structure of their networksrevealed that a strong ties network architectureand a dual network architecture had alternatedover a time lapse of more than 30 years, and thatthe former had characterized the opaque phaseswhile the latter had prevailed during the brilliantphases.

STAGE TWO

In search of an explanation of an apparent asso-ciation between the structure of the three net-works under investigation and the innovative per-formance of their lead firms, following a cus-tomary path in network research I started fromthe dyad level of analysis. Here, specifically atthe intersection with the firm level, I realized thepotential of strong dyadic ties for innovation. Ialso noticed that, in my three cases, this potentialhad spread across both the opaque and the bril-liant phases. However, moving upward from thedyad level to the network level and focusing onthe intersection between the network level and thefirm level I found that, when strong ties networkshad prevailed (i.e., during the opaque phases), thepotential of strong dyadic ties for innovation hadbeen partially offset by the pitfalls of a strong tiesnetwork architecture, thereby slowing down theinnovative performance of the three lead firms.Conversely, when the lead firms had leverageddual networks (i.e., during the brilliant phases),the advantages of a large periphery of weak tieshad countered the potential disadvantages of astrong ties network, and the benefits of a networkarchitecture combining the strengths of strong andweak ties had emerged, thereby leading to out-standing innovation. Following this line of expla-nation, I outline below the strengths of strong ties,the weaknesses of a strong ties network, and thestrengths of a dual network.

Strengths of strong ties

The fieldwork suggests the following three cat-egories of strong ties’ strengths to explain therelevant contributions of strong dyadic ties withexternal designers to the lead firms’ innovativeperformance across the opaque and the brilliantphases.

The first category refers to mutual knowledge.Manufacturers and design firms involved in strongties accumulated over time a thorough reciprocalknowledge of each other’s resources, technicalknow-how, design competencies, and organiza-tional routines, together with a deep mutual under-standing of cultural traits and long-term objectives.This impacted positively the lead firms’ inno-vative outcomes in a number of ways. First, itallowed the manufacturers to select appropriatepartners for additional joint-design agreements in



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598 A. Capaldo

a way that significantly increased the probabil-ity that the resulting products would be coherentwith the company’s overall design philosophy orwith a particular style. Second, it reduced time tomarket by facilitating and speeding up interorga-nizational interaction along the entire new prod-uct development process. Third, a deep mutualknowledge increased joint-design effectiveness byputting the design firms in a favorable positionto either (a) pick up and interpret new productideas that, while shared among the organizationalactors across the allied firm in latent forms, wouldhardly take shape without an external facilitator, or(b) advance totally new product ideas able to sus-tain the partner’s competitive orientation or sup-port change in its business strategy, or even todictate major developments in its corporate strat-egy (e.g., entering a new business).

Thus, according to a manager from the R&DDepartment of Cassina:

The overall quality of a joint-design process isstrongly affected by a history of cooperation. In ourexperience, the best results are typically attainedafter the parties have developed a thorough mutualunderstanding over time. . . . At first, wariness pre-vails and neither we nor external designers giveourselves away. Later on, as knowledge of the peo-ple involved in the relationship deepens and trustdevelops, formal patterns of interaction are usu-ally set aside and we get on the same wavelengthwith our partners. At this point, real collaborationtakes off and new products take shape smoothly,capitalizing on lessons learned and on ‘broadband’information exchange.

The second category of strong ties’ strengthsincludes the importance of interorganizational trustand reciprocity, and of the underlying interper-sonal relationships between individual membersof the partnered organizations. As the Director ofCassina’s R&D Department put it:

Mutual trust, reciprocity between partners, andfeeling among individuals: these are the ingredientsfor successful partnerships. . . . Time and repeatedinteractions are essential to develop such favorableconditions. First-class innovation will be a logicalconsequence.

Interorganizational trust and its leverage onknowledge sharing and innovation deserve specialattention. Both manufacturers and external design-ers involved in strong, trust-based relationshipswere willing to pool their assets and to share

their knowledge with partners in the awarenessthat proprietary know-how would not be absorbedand exploited opportunistically by the other party,let alone transferred to competitors. Indeed, theparties’ concern for reputation induced manufac-turers to carefully avoid unilateral exploitations ofnew product ideas suggested by external designers,while also preventing designers from leaking theirpartners’ industrial secrets and strategic plans tocompetitors. Analogously to what Hagen and Choe(1998) reported in their study of buyer–seller rela-tionships in the Japanese auto industry, my directobservations during the ‘design reviews’ and myinformal conversations with the three lead firms’CEOs and with external designers highlighted theway societal sanctioning and the rapid spread-ing of reputation in social networks discouragedopportunistic behaviors on either side, thereby pro-moting mutual trust and hence open-ended andknowledge-intensive cooperation.

In addition, the sample manufacturers engen-dered trust in their strong relationships with designfirms proactively through informal agreements bywhich external designers agreed to joint-designgiven products (e.g., sofas and/or tables, or indoorand/or outdoor lighting appliances) exclusivelywith specific manufacturers. Such informal safe-guards had positive effects on innovation pro-cesses and their outcomes by encouraging themanufacturers to participate in knowledge-transferactivities. At the same time, being strictly limitedto certain product categories, such exclusive agree-ments did not jeopardize the design firms’ ability tocome up with new ideas by brokering knowledgeacross diverse industries.

Furthermore, social and affective contents (andsometimes real friendship) flowed from the inter-personal linkages underlying the interorganiza-tional relationships and were nourished throughthat deep feeling of challenge that joins individ-uals involved in the development of new prod-ucts. Together with the awareness of partner’strustworthiness resulting from previous long-livedand repeated interactions, those contents encour-aged participants in strong ties to increase theiremotional investments in the relationship and tocooperate well beyond contractual provisions inthe pursuit of innovation. Once such a collabora-tive atmosphere had been created, the entire man-ufacturer’s organization became ready to join theexternal designer in testing ground-breaking designapproaches and developing innovative products.



At the same time, the designer became willingto serve as a ‘sheet anchor’ for his/her partner(e.g., by designing new products in record time,in order to meet urgent customer needs or coun-teract unexpected competitor moves), or even toaccept that his/her ‘bold projects’ might be setaside or delayed for competitive or market reasons.While signaling open-ended and effective coopera-tion, these emerging patterns of mutual adjustmenthelped partners to find the right balance betweentheir innate propensity to explore new trajectories,leading to a relentless search for path-breakinginnovation, and more conservative approaches pur-suing competitive effectiveness and easier accep-tance of new products by customers, with positiveeffects on the overall innovation performance.

The third category of strong ties’ strengthsincludes actions taken and investments made bythe participating organizations in the belief thatinterfirm alliances can positively influence per-formance on both sides and that the destinies ofpartners tied by a strong relationship are deeplyintertwined. External designers involved in strongties were willing to promote new products towardcustomers, to deliver market feedback to the man-ufacturers, to suggest how to improve existingproducts and to submit new product ideas to theirpartners. While clearly driven by immediate eco-nomic incentives, these actions were also intendedto be acts of commitment, in response to whichthe manufacturers were ready to allocate resourcesto the joint definition of new product styles orto finance marketing initiatives in support of theirpartners’ identity, in the awareness that two orga-nizations tied by a strong relationship build eachother’s reputations. Thus, both the partners’ levelof resource commitment to the relationship and thelead firm’s potential for innovation grew substan-tially.

In particular, relation-specific investments inphysical and human assets were made on eitherside in a way that tailored processes, organiza-tional competencies, and human skills to particularpartners, with positive effects on the pursuit ofinnovation. The lead firms acquired machinery andtechnical know-how to employ their design part-ners’ favorite materials, while at the same timeexternal designers learned to specialize in design-ing product lines included in the manufacturers’catalogs, or to develop idiosyncratic skills neededto exploit exclusive technologies mastered by theirpartners. The rationale for these investments lay

in interorganizational trust and interpersonal rela-tionships, which fostered a strong confidence thatthey would be reciprocated by the other side andthat the resulting advantages would be sharedbetween partners. Through such investments, man-ufacturers and designers signaled to each othertheir willingness to prolong their cooperation andstimulated further reciprocal acts of commitment,thereby driving the relationships further along theirdevelopmental processes (Anderson and Weitz,1992; Ring and Van de Ven, 1994) and ultimatelystrengthening the ties at both interorganizationaland interpersonal levels.

Weaknesses of a strong ties network

Despite the advantages of strong dyadic ties, myfieldwork suggests that the ‘dark side’ of a strongties network may explain an apparent irony—thatis, why the innovative performance of each sam-ple lead firm slowed down during time periods inwhich strong ties accounted for the dominant pro-portion of both total network membership and thelead firm’s alliance activity.

First, when these conditions occurred, and henceweak ties played a marginal role, the three man-ufacturers found themselves locked in a narrowcircle of strong ties, and thus dependent on theinspiration of only a small number of externalsources of creativity. This constrained the leadfirms’ ability to gain access to novel ideas and togenerate truly new products, which in turn resultedin the ‘opaqueness’ of the corresponding histor-ical phases. In addition, the small network sizereduced the lead firms’ bargaining power in eachsingle relationship and increased their risks of fail-ure should network players be lost.

Second, when playing the leading role in astrong ties network, the three manufacturers foundthemselves at least partially locked out of theinnovative stimuli continuously arising within the‘design world.’ Moreover, they also lacked thatlarge and diverse knowledge base needed to evalu-ate new external designers thoroughly, or to appre-ciate their potential for contributing to the pursuitof innovation. At the same time, the flexibilityof the lead firms’ organizational routines to inter-act with multiple asymmetric partners declined.All this limited the firms’ ability to perceive newtrends and to keep abreast of technological evolu-tions, while also threatening their cultural attitudetoward, and organizational reactivity to, change.


600 A. Capaldo

Third, for the three lead firms, blindness towardnew partners also decreased strategic responsive-ness to social and economic changes. Marketingstrategies became overfocused on the existing tar-gets and risks of losing contact with emergingcustomer groups increased. As a result of such along distance from new market trends, the bestchances to anticipate market evolution, to sensenew opportunities, and to create new forms, func-tions, and lifestyles were missed. In addition, thelead firms’ reputations suffered, and the compa-nies and their managers became portrayed as beingopposed to newness and bold innovations, furtherundermining the firms’ competitiveness.

The weaknesses inherent in a strong ties networkare summarized in the words of iGuzzini’s CEO:

Although the history of iGuzzini has been char-acterized by some very close relationships withexternal designers, and even though for some briefperiods we yielded to the temptation to tie our-selves tightly to just one or a small number ofexternal designers, it was clear for me from thevery beginning that gambling on a few such part-nerships wouldn’t be the best strategy in the longrun. How would we get to know of the latest tech-nological innovations and their applications? Howwould we find out the hottest trends in forms? Howwould we be aware of the tastes and needs of dis-parate customer groups in different continents? . . .To do these things well, we need to maintain manyand diverse ‘antennae’ in multiple directions, let-ting our partners smell out new trends or gatherinnovative stimuli from multiple sources.

Strengths of a dual network

During the brilliant phases, the three design-intensive furnishings manufacturers avoided theweaknesses of a strong ties network by leverag-ing a dual network architecture including a largeperiphery of weak ties. The following advantagesof such an alliance behavior worked together togenerate superior innovation.

First, a large number of weak ties eliminated thehazards of being locked in a restricted number ofrelationships. Interestingly, and consistently withprevious research (Powell et al., 1996; Simonin,1997), the interviewees also argued that interact-ing with several design firms fostered learningprocesses, resulting in rapid accumulation of bothindividual skills and organizational capabilities tocreate and manage interfirm collaborative relation-ships, thus laying the foundations for further net-work development.

Second, contributions from numerous partnersamplified variance within the network. The threemanufacturers purposely created a large peripheryof weak ties to collaborate with external designersthat employed diverse technologies and materi-als, and to come into contact with a variety ofdesign approaches, expressive languages and styles(Cassina), or at least to experiment with multipledifferent interpretations of the company’s designphilosophy (B&B Italia) or even of a well-definedstyle (iGuzzini). Moreover, repeated interactionswith a large number of network nodes forced thelead firms to master diverse approaches to organiz-ing joint-design activities, thereby enhancing theflexibility of both their internal procedures androutines for interorganizational interaction. Thus,weak ties avoided redundancy within the network.Over time, they made considerable contributionsto the lead firms’ knowledge base, which in turnincreased the firms’ attractiveness toward externaldesigners, whether they were already part of thenetwork or potential partners.

Third, a major effect of the resulting inwardlydiverse networks was an increasing openness ofboth the overall networks and their leading actorstoward new market trends. During the brilliantphases, while entrusting strong ties with the pri-mary task of satisfying already targeted customers,the three manufacturers tended to leverage theirnumerous weak contacts to approach ‘new’ (i.e.,previously untargeted) market segments, to openwindows on trendsetter geographical markets (e.g.,the United States) and customer groups (e.g., the‘hippies’ during the late 1960s, or the ‘yuppies’around the mid 1980s), and to throw sensors intoemerging geographical markets (e.g., China), prod-uct markets (e.g., outdoor lighting), and customergroups (e.g., new generations). Overall, weak tieswere frequently employed to support proactivestrategies aimed at nurturing new lifestyles throughinnovative product concepts jointly conceived withexternal designers.

In summary, during the brilliant phases, thesample lead firms deliberately created and nurtureda large periphery of heterogeneous weak ties withthe aim of escaping redundancy and increasing thediversity of their networks. Thus, they avoidedthe risks inherent in a strong ties network whilecontinuing to enjoy the strengths of strong ties.According to the Director of B&B Italia’s R&DDepartment:



Our mission is to generate product innovationrelentlessly, and therefore we cannot concentrateour partnering efforts on a few strong contactsexclusively. . . . Strong ties are valuable referencepoints, but we must not avoid continuously build-ing a large number of new alliances with designfirms that have the potential to carry us on newpaths. It’s a matter of bargaining power. . . . Aboveall, it’s a matter of flexibility: these [weak] rela-tionships allow us to stay flexible toward multipleand fast-changing product technologies, materials,design approaches and procedures, styles, markets,and customers’ needs.

DISCUSSION

This study examines how three lead firms managedtheir strategic networks of knowledge-intensivealliances over more than 30 years. My longitudinalcase studies illustrate the role of strong dyadic tiesin sustaining lead firm innovation during the entireinvestigation period. They also show that, overtime, the sample lead firms alternated two differentnetwork architectures, whose different impact oninnovation is a major explanation of a successionof opaque and brilliant phases in the firms’ his-tories. The overall theoretical contribution of thispaper is discussed in the present section and sum-marized in Figure 2, which sketches out a cross-level preliminary model of the impact that strongdyadic ties, a strong ties network, and a dual net-work exert on the lead firm’s innovative capabilityover time.

At the dyad level of analysis, and focusingspecifically on the intersection with the firm level,the cases suggest that the strengths of strongties—mutual knowledge, social contents, andrelation-specific investments—sustain the leadfirm’s capability to innovate repeatedly. Besidesoperating individually, the three sources of strongties’ strengths reinforce each other over time in avirtuous circle. Indeed, a thorough mutual knowl-edge is a prerequisite for social contents to developin interfirm alliances, as well as for relation-specific investments. In turn, the development ofthe social aspects of economic exchange not onlycontributes to the deepening of mutual knowl-edge by means of ‘fine-grained information trans-fer’ (Uzzi, 1997) concerning proprietary know-how and confidential information, but also encour-ages the participating organizations to intertwinetheir destinies by investing in relation-specificassets (Dyer, 1996). Relation-specific investments

in physical and human assets increase the eco-nomic interests at stake and, when balancedbetween partners, demonstrate mutual commit-ment. This further stimulates the development ofsocial contents and sets the relationship on tracksof reciprocity, laying the foundations for futureinteractions, and hence for the deepening of mutualknowledge. Finally, as mutual commitment, fueledby the making of relation-specific investments onboth sides, increases along the relationship devel-opmental process, mutual dependence between theexchange partners also grows incrementally, inturn exerting a positive effect on the relationshipvalue creation (Blankenburg Holm, Eriksson, andJohanson, 1999).

Long-lasting, frequent, and intense dyadic inter-organizational collaboration is the fundamentaldriver of the process outlined above, whereingrowing trust is an intermediate product that leadsthe process into subsequent cycles, and anincreased innovative capability is the major out-come at the lead firm level. Over time, as strong-tied partners interact repeatedly, they learn abouteach other, while the social side of economicexchange develops (Larson, 1992) and special-ized knowledge is accumulated (Doz, 1996; Dyerand Singh, 1998), thereby further strengtheningthe tie. Trust stimulates close interpersonal inter-action and mitigates fear of opportunistic behav-iors (Kale et al., 2000; Zaheer et al.,1998), help-ing partners to overcome the organizational safe-guards that companies involved in knowledge-intensive alliances typically set up to limit uncon-trolled information disclosure. The resulting cross-fertilization of the participating organizations’knowledge bases is a preliminary condition forknowledge creation—and hence for innovation—to occur in interfirm alliances.

Trust emerges from repeated interactions (Good,1988; Gulati, 1995), as interfirm relationshipsevolve through their developmental processes(Ring and Van de Ven, 1994). In addition, priorresearch shows that firms that hold the reins ofnetworks purposely build interorganizational trustto facilitate interfirm knowledge transfer (Dyer andNobeoka, 2000). Coherent with this, my findingssuggest that lead firms can stimulate innovationby deliberately fostering an atmosphere of trustwithin their network ties through exclusive agree-ments whose scope is narrow and well defined.


602 A. Capaldo

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Such arrangements promote open-ended coopera-tion and knowledge sharing within dyadic relation-ships without discouraging partners from brokeringacross diverse knowledge domains outside the rela-tionships.

The above arguments suggest the followingproposition:

Proposition 1: Over time, strong dyadic tiesexert a positive impact on the innovative capa-bility of the lead firm in an alliance network bypromoting a virtuous circle in which the deep-ening of mutual knowledge, the development ofsocial contents between partners, and the mak-ing of relation-specific investments on both sidesreinforce each other, resulting in trust-basedknowledge-intensive relationships.

Lead firms that take advantage of the strengthsof strong ties, however, may also face the weak-nesses of a strong ties network. The danger ofbeing locked in a narrow circle of strong ties andthe risk of becoming unable to face technologi-cal discontinuities or profit from new opportuni-ties—whether they spring from heterophilous rela-tionships or new market trends—are major hazardsfor the leading actor in a strong ties network. Infact, they may jeopardize the lead firm’s ability togenerate, or to respond to, change. This is also dueto the marginal role weak ties play in a strong tiesnetwork, preventing the periphery of the networkfrom exerting significant influence on innovation.

As Burt (1992) pointed out, network size anddiversity are major concerns in network man-agement (see also Baum et al., 2000): numerousrepeated ties to too small a number of partnersgenerate isomorphism within the network, therebydecreasing network diversity and the lead firm’saccess to nonredundant knowledge. Thus, the haz-ards of a strong ties network not only operateindividually, but also reinforce each other overtime in a vicious circle in which long-lasting, fre-quent, and intense interorganizational collaborationwith a small number of core contacts becomes thefundamental driver, the decreasing growth rate ofthe lead firm’s knowledge base is an intermedi-ate product that leads the process into subsequentcycles, and a diminished innovative capability isthe major outcome at the lead firm level.

Previous research suggests a positive relation-ship between number of alliances and organi-zational innovation output (Ahuja, 2000a; Shan,

Walker, and Kogut, 1994). Network membershipand tie modality matter too (Gulati et al., 2000).Thus, the more the lead firm is strong-tied toa small number of homogeneous contacts, themore it becomes blind toward the possibilities ofnew partners, and hence the more homophily andoverembeddedness tend to slow down the devel-opment of its knowledge base. At the same time,the flexibility of the lead firm’s internal proceduresand organizational routines for interfirm interactiongradually decreases. Where the lead firm system-atically relies on its network to detect customers’needs, the small network size and an inadequateorganizational flexibility, which hinders interac-tion with new partners, will also lead the firmand its network to become out of step with marketdemands. Following this path, the growth rates ofboth the lead firm’s knowledge base and its cus-tomer base rapidly decrease, and hence the firm’sattractiveness toward potential partners becomesseriously damaged, preventing the organizationfrom gaining access to fresh external sources ofcreativity, which in turn further insulates the net-work from new market trends. Thus, a spiral is trig-gered off which leads over time to a small, homo-geneous, and closed network that exerts a negativeimpact on the lead firm’s innovative capability.Therefore, the following proposition is advanced:

Proposition 2: Over time, a strong ties net-work architecture exerts a negative impact onthe innovative capability of the lead firm in analliance network by promoting a vicious circle inwhich reducing numbers of contacts, decreasingflexibility for collaboration with new partners,and diminishing responsiveness to new markettrends reinforce each other, resulting in a small,homogeneous, and closed network.

The above observations are especially relevantto firms, such as the three design-intensive manu-facturers in the present study, that rely on large-scale interfirm collaboration to keep pace with con-tinuous technological and market developments,to sustain their organizational flexibility, and topick up and develop new product ideas. Duringthe opaque phases, the sample firms suffered fromthe weaknesses of their strong ties networks. Con-versely, during the brilliant phases, they enjoyedthe strengths of strong ties and avoided the weak-nesses of a strong ties network architecture byleveraging dual networks, which saw their core


604 A. Capaldo

of strong ties integrated with a large periphery ofweak ties, thereby increasing both network sizeand diversity. Such strategic behavior reveals alead firm’s distinctive relational capability, onethat capitalizes on the strengths of a dual net-work architecture to create favorable conditions forsustained competitive advantage based on superiorinnovation.

For the lead firm in a dual network, the increasein network size associated with having numerousweak ties eliminates the hazards of small-numbersbargaining. A large number of partners reducesindeed the vulnerability of the firm to its exter-nal sources of innovation failing, drying up, orexiting the network, thereby enhancing the com-pany’s bargaining power in each dyad. At thesame time, a large periphery of weak ties sig-nificantly increases network diversity. Thus, con-tinuous interplay between a growing number ofcontacts and an increasingly heterogeneous webof partners generates over time a large, diverse,and open network that exerts a positive impacton the innovative capability at the lead firmlevel. Network diversity is key. My three caseshave highlighted three major sources of networkdiversity and their advantages for the lead firmin a dual network. These three sources resultfrom the network nodes’ heterogeneity in termsof (1) technical skills and organizational compe-tencies, (2) internal procedures and routines forinterorganizational interaction, and (3) market per-spectives.

Thanks to the first source of network diversity,the leading actor can rely on multiple differentsources to access various skills and mobilize het-erogeneous competencies (Grant and Baden Fuller,2004), as well as to learn new knowledge (Beck-man and Haunschild, 2002). In particular, whenlearning occurs, the lead firm’s absorptive capac-ity is enhanced, thereby increasing the organiza-tion’s capability to innovate (Cohen and Levinthal,1990). In addition, the company’s attractivenesstoward both existing and potential partners isimproved, creating fertile ground for further net-work development.

The second source of network diversity forcesthe lead firm to adapt its own internal proceduresand to develop flexible routines for knowledge-intensive interorganizational interactions. In turn,this enhances the organization’s capability to inter-act effectively with a large number of hetero-geneous partners. The resulting flexibility allows

the lead firm to integrate and recombine knowl-edge inputs from multiple heterogeneous networknodes, thereby actualizing the potential for knowl-edge creation residing in its alliance network. Flex-ible routines also allow the lead firm to adjustthe composition of the network quickly, therebyincreasing the firm’s ability to adapt in the faceof environmental changes which might render itspartners’ capabilities outdated.

The third source of diversity offers the leadfirm in a dual network valuable intelligence of,and different angles on, the preferences of bothalready-targeted customer groups and geographi-cal markets or market segments beyond its usualscope. This can support the company’s existingmarketing strategy and/or drive it toward new tar-gets, opening the overall network and its leadingactor toward new market trends.

The above three sources of network diversityand their advantages reinforce each other overtime. The flexible (inter)organizational routinesdeveloped from interactions with multiple hetero-geneous partners allow the lead firm in a dualnetwork to make the most of its web of contacts’potential both to learn new knowledge by interact-ing with its partners, and to enlarge its customerbase. As the lead firm repeatedly absorbs, fromdifferent partners, information on new customergroups and knowledge to satisfy their needs, avirtuous co-evolution develops between the firm’scustomer base and its knowledge base, thus layingthe foundations for sustained competitive advan-tage based on a truly dynamic innovative capabil-ity.

The above findings and arguments suggest thefollowing propositions:

Proposition 3: Over time, a dual network archi-tecture exerts a positive impact on the innovativecapability of the lead firm in an alliance net-work by promoting a virtuous circle in whichgrowing numbers of contacts and increasing net-work diversity reinforce each other, resulting ina large, diverse, and open network.

Proposition 4: The leveraging of a dual networkarchitecture is a distinctive relational capabilitythat allows the lead firm in an alliance networkto gain and sustain competitive advantage basedon a dynamic innovative capability.



CONCLUSION

This paper contributes to the growing debateon strategic management of knowledge-intensivealliance networks by taking the perspective of thelead firm and stressing the importance of relationalcapabilities as dynamic sources of competitiveadvantage. In a recent contribution, Gulati et al.(2000: 207) pointed out that the structural pat-tern of a firm’s relationships can be an inimitableresource. The present research shows that, in orderto exploit the potential for competitive advantageembodied in interorganizational network ties, leadfirms should manage the structure of their net-works carefully. Founding upon comparative lon-gitudinal case study research of three lead firms, Isubmit that the ability to integrate a large peripheryof heterogeneous weak ties and a core of strong tiesis a distinctive relational capability, one that pro-vides fertile ground for leading firms in interfirmnetworks to gain competitive advantages whosesustainability is primarily based on the dynamicinnovative capability resulting from leveraging adual network architecture.

This study is aimed at contributing to theorybuilding in the field of interfirm networks. Theplausibility of the propositions presented in thepreceding section has been partly established inthe empirical research analyzed here. Testing andrefinement await future research. Focusing on thedifferent impact that strong dyadic ties, a strongties network, and a dual network exert on the leadfirm’s innovative capability, I have advanced across-level preliminary model to explain why andhow independent dyad- and network-level vari-ables exert a causal influence on a dependent firm-level variable. Conversely, the antecedents of dif-ferent network architectures were beyond the scopeof this paper. However, my fieldwork suggests thatthe three alliance networks and their structures co-evolved with both environmental conditions andthe overall strategies of their leading actors. Futurestudies will have to focus on such co-evolutionto shed light on the exogenous and endogenouspreconditions underlying the two archetypical net-work architectures discussed here. This may helpexplain why and how, as happened in my threecases, suboptimal network architectures can tem-porarily overwhelm more beneficial ones.

Some caveats may be in order, given that myarguments emerge from a limited number of casestudies. Moreover, whereas the theoretical and

practical relevance of strategic network manage-ment asks for research in the field of relationalcapabilities, the case study might not be consideredthe most appropriate research strategy. However,following Eisenhardt (1989), I believe that the rela-tive lack of empirical research on the topic justifiesmy methodological choice, while the multiple-casecomparative approach adopted here contributes toincrease the robustness of my findings and propo-sitions.

Practicing managers and entrepreneurs shouldconsider that strategic networks can provide firmswith tangible and intangible resources needed tocompete. Specifically, the research in this paperillustrates that, where the capability to innovaterepeatedly is a prerequisite for competing success-fully, firms benefit from business ideas in whichsystematic connections to innovation sourcesbeyond the organization’s boundaries are distinc-tive components from the very outset.

The three cases also offer prescriptions forstrategic network maneuvering. Albeit strong tiesyield substantial benefits, the lead firm may finditself closed in an inwardly focused network.Instead, adopting a dual network architecture al-lows the lead firm to rely on a narrow core of long-lasting, repeated, trust-based relationships withsimilar partners for exploitation purposes whileat the same time exploring more distant knowl-edge areas, different organizational routines, andnew markets through a large periphery of diverse,weak relationships. Thus, leveraging a dual net-work allows the lead firm to tackle the present atthe same time as it paves the way for the future,and to avoid inertia by staying flexible towardinnovative technologies, heterogeneous partners,and new market trends. The two parts of a dualnetwork have to be managed in different ways,however. Therefore, studying the distinctive orga-nizational routines that undergird strategic man-agement of a dual network’s core and periphery isa compelling avenue for further research.

I conclude by suggesting some other impor-tant aspects of this paper. First, I have advancedan operationalization of tie strength that, althoughspecifically focused on interorganizational ties,takes account of the linkages between interor-ganizational and interpersonal relationships. Sec-ond, I have shown that simultaneous and explicitconsideration of multiple levels of analysis, and‘dialogue’ between research on different levels,


606 A. Capaldo

can enrich our explanations of intrinsically cross-level (inter)organizational phenomena. Using thelead firm’s innovative capability as my outcomevariable, I have first analyzed the strengths ofstrong dyadic interfirm ties. Then, exploring thelinkages between the dyad level and the networklevel has allowed me to discuss why and howthe strengths of strong ties can be offset by thepitfalls of a strong ties network or, conversely,reinforced by the advantages of a dual network.Thus, besides providing additional support for Gra-novetter’s (1973) strength-of-weak-ties argument,this study adds that, when the lead firm devel-ops the relational capability to integrate strong andweak ties within the same network architecture, thestrengths of weak ties counteract the weaknessesof a strong ties network, and thus the strengths ofa dual network emerge.

ACKNOWLEDGEMENTS

An earlier version of this paper was presented atthe 2001 Academy of Management Conference.I am grateful to Gianni Lorenzoni, Peter SmithRing, and Maurizio Sobrero for insightful com-ments. I also thank Associate Editor Ed Zajac andtwo anonymous SMJ reviewers whose construc-tive feedback helped to improve the paper. Conver-sations with Andrew Pettigrew in the initial stagesof the research project out of which this paper grewprovided useful methodological insights. Financialsupport from the Italian Ministry of University andScientific and Technological Research (MURST)(’PRIN 1999’—rec. n. 9913492974 004) and theItalian NationalResearch Council (CNR) (research title: ‘TheStrategic Management of Interfirm Networks’) isgratefully acknowledged.

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