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Citation: Lipparini, A., Lorenzoni, G. & Ferriani, S. (2014). From core to periphery and back: A study on the deliberate shaping of knowledge flows in interfirm dyads and networks. Strategic Management Journal, 35(4), pp. 578-595. doi: 10.1002/smj.2110
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Strategic Management JournalStrat. Mgmt. J., 35: 578–595 (2014)
Published online EarlyView 21 March 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smj.2110
Received 24 July 2010 ; Final revision received 31 July 2012
RESEARCH NOTES AND COMMENTARIES
FROM CORE TO PERIPHERY AND BACK: A STUDY ONTHE DELIBERATE SHAPING OF KNOWLEDGE FLOWSIN INTERFIRM DYADS AND NETWORKS
ANDREA LIPPARINI,1* GIANNI LORENZONI,1 and SIMONE FERRIANI1,2
1 Department of Management, University of Bologna, Bologna, Italy2 Cass Business School, City University London, London, U.K.
We study 892 Italian motorcycle industry projects carried out via 184 different buyer–supplierand supplier-supplier relationships to provide evidence on the knowledge dynamics occurring indyads and networks and to understand the underexplored but important (perhaps even dominant)leading role that some firms play in the evolution of networks and interfirm learning processes. Wedevelop a multiphase model which, from a multilevel perspective addressing different relationalsubsets, suggests how firms can best organize to generate and exchange knowledge efficiently.We argue that extant theoretical perspectives can profitably draw on our findings to strengthentheir dynamic components and help them explain the widely diffused ‘exploring through partner’strategies more effectively. Copyright 2013 John Wiley & Sons, Ltd.
INTRODUCTION
Both executives and academics have recently iden-tified knowledge as one of the most importantfactors contributing to firms’ ability to achieve sus-tainable competitive advantage (Dyer and Singh,1998; Dyer and Nobeoka, 2000; Zhao, Anand, andMitchell, 2005). At the same time, a growing bodyof research has come to consider networks as anappropriate unit of analysis (Powell, Koput, andSmith-Doerr, 1996; Kogut, 2000) and to exam-ine the question of where a firm should drawits boundaries (Parmigiani and Mitchell, 2009)on the understanding that ‘where boundaries are
Keywords: knowledge exchange and creation; interfirmnetworks; core and peripheral firms; knowledge-enhanc-ing practices; motorcycle industry*Correspondence to: Andrea Lipparini, Department of Manage-ment, University of Bologna, Via Capo di Lucca, 34 – Bologna,Italy. E-mail: [email protected]
drawn affects the value placed on knowledge andits usefulness’ (Argote, McEvily, and Reagans,2003: 574). This work has shown how knowl-edge and other critical resources increasingly spanfirm boundaries so that the advantage of a sin-gle firm is often linked to those of the networkof ties in which it is embedded (Dyer and Singh,1998). In particular, research rooted in innova-tion literature (Powell et al., 1996; Zhao et al.,2005) and in buyer–supplier relationships (Kotabe,Martin, and Domoto, 2003) has emphasized theincreasing importance of networking, alliances andidiosyncratic interfirm relations (Martin, Mitchell,and Swaminathan, 1995), and the advantages ofadopting a cooperative mode for knowledge cre-ation (Mesquita, Anand, and Brush, 2008). Strate-gic literature’s focus on knowledge creation andmanagement has been expanding in unprecedentedfashion, so that the key knowledge-based ques-tions companies face are not only how to organizethemselves to exploit their already developed
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.This is an open access article under the terms of the Creative Commons Attribution License, which permits use,distribution and reproduction in any medium, provided the original work is properly cited.
Research Notes and Commentaries 579
knowledge or capabilities, but also ‘how to orga-nize to efficiently generate knowledge and capa-bility’ (Nickerson and Zenger, 2004: 617).
Our multiple case, inductive study (Eisenhardt,1989) attempts to answer the above question.We present a multiphase model of interfirmknowledge creation and exchange across dyadsand networks and discuss the important (per-haps even dominant) role that buying firmsplay in the evolution of networks and of inter-firm learning processes, which has hitherto beenunderexplored in the strategic literature. Weposit that networks become viable organizationalforms for sharing and generating valuable knowl-edge when a set of purposefully implementedknowledge-enhancing practices—which we defineas distinctive patterns of action and interactionbetween core firms—‘buyers’—and peripheralfirms—‘suppliers’—that enable the exchange,recombination, and co-creation of specializedknowledge—allow firms to leverage knowledgelocated beyond their organizational boundaries.1 Inparticular, we focus on a total of 892 projects asso-ciated with the design and/or manufacture of com-ponents for motorbikes and/or scooters in the Ital-ian two-wheeler industry. These projects involved17 leading motorcycle manufacturers—core buyerfirms who were responsible for setting up andsubsequently ‘orchestrating’ dyads and networks(Dhanaraj and Parkhe, 2006)—and their (periph-eral) first-tier suppliers.
CONCEPTUAL BACKGROUND
Although prominent firm perspectives have con-tributed greatly to explain how firms achieve sus-tainable competitive advantage, they still overlookthe fact that, increasingly, even unique resourcesspan firm boundaries and can be selectively trad-able through a network of firms (Kogut and Zan-der, 1992; Gulati, 1999). Even contributions thathave significantly extended resource-based reason-ing (Barney, 1991; Peteraf, 1993) and are rooted inknowledge and capability-based views in strategy(Kogut and Zander 1992; Conner and Prahalad,
1 Throughout the article, we make use of the core peripherypattern to convey the particular situation in which core firms,which possess prominence gained through relational skills andtheir central position in network structures, leverage theirposition to harness the knowledge dispersed among peripheralfirms.
1996; Teece, Pisano, and Shuen, 1997; Felin andHesterly, 2007) share a main focus on intrafirmtransfers of existing knowledge (Hansen 1999; Tsai2001; Reagans and McEvily, 2003; Levin andCross, 2004) and are less well equipped to analyzeknowledge transfer and creation across fully inde-pendent entities (which have become significantlymore common over a wide range of industries,from automobiles to semiconductors) (Nickersonand Zenger, 2004; Hansen, Mors, and Løvas,2005; Mesquita et al., 2008). A growing numberof empirical studies rooted in innovation literature(Powell et al., 1996; Zhao et al., 2005), and espe-cially those adopting a relational perspective (Dyerand Singh, 1998), explicitly consider the collabo-rative network, rather than the single firm, as thelocus for learning and innovation. In particular,research on buyer–supplier networks in the auto-mobile industry (Dyer, 1996; Osborn and Hage-doorn, 1997; Argote et al., 2003) has shown howthe extensive involvement of suppliers in productand process development has given lead assem-blers faster product development cycles, lowercosts, better end product quality (Womack, Jones,and Roos, 1990; Dyer and Nobeoka, 2000), andfaster problem solving (Takeishi, 2001). The ideathat networks are critical for knowledge creationand exchange is corroborated by studies conductedfrom knowledge transfer perspectives (Tsai, 2001;Reagans and McEvily, 2003; Inkpen and Tsang,2005). Systematic evidence from this researchstream indicates that networks with substantialknowledge transfer mechanisms between man-ufacturers and suppliers out-innovate relationalsets with less well-developed knowledge-sharingroutines.
Following Kogut (2000), we see networks as theoutcomes of generative rules of knowledge coordi-nation, which constitute capabilities (e.g., speedyresponse to change, resource orchestration, etc.)generating relational rents, which can be subject toprivate appropriation. Our study focuses on mul-tiple transactions and on those deliberate and pur-poseful actions designed to facilitate knowledgegeneration and mobility across networks’ bound-aries, which are central to their ability to co-innovate and so co-create value (Zhao et al., 2005).While most studies focus on ties with genericallydefined content, we disentangle the intertempo-ral processes of knowledge creation and exchangebetween organizations and adopt a multilevel per-spective that addresses three different subsets
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
580 A. Lipparini, G. Lorenzoni, and S. Ferriani
of relationships—R&D, operations, and other up-and downstream activities. We also investigatelearning processes and knowledge-related activi-ties involving both sides of the dyad and considerthem as both knowledge transmitters and recipi-ents. Although several studies have included bilat-eral (buyer and supplier) analyses (e.g., Zanderand Kogut, 1995; Takeishi, 2001; Kotabe et al.,2003), they have considered knowledge flows onlyas unidirectional—one unit providing and onereceiving—and such perspectives clearly limit ourunderstanding of cases where firms both provideand receive knowledge. Finally, we show how theeffective creation and extraction of network valuehinges on the purposeful enactment by core firmsof practices designed to lead and facilitate knowl-edge sharing and deployment.
METHODS
Research design, setting, and sampleconstruction
Our inductive, multiple case study (Eisenhardt,1989) examines the Italian powered two-wheelerindustry, which we deemed appropriate for sev-eral reasons. First, product architecture: motorcy-cles and scooters2 are made of dozens of mod-ules and subassemblies whose development andmanufacture requires diverse and specific know-how and expertise (Helfat, Lipparini, and Verona,2011). Second, the level of product innovationinvolved is appropriate: manufacturers are con-tinually challenged by the introduction of newmaterials—plastics, titanium, carbon fibers, lightalloys, etc.—into frames and components, aswell as the need to meet changing environ-mental regulations (Helfat et al., 2011). Third,the intense industrial process innovations, whichrequire manufacturers to adopt state-of-the-artequipment and R&D practices and to base theirmanufacturing activities on leading-edge technolo-gies (Gavetti, 2001). Fourth, the size of Italy’sdomestic market—the largest in Europe in termsof powered two-wheeler production (nearly 55%),registrations (26.7%), and numbers of motorcy-cles in use (26%)—and its competitive position as
2 A scooter is a small-engined, two-wheeled motor vehicle withcertain design characteristics such as a step-through frame, smallwheels, and an automatic transmission.
Europe’s leading exporter, headed only by Japanand Taiwan in world rankings (ACEM - Associa-tion des Constructeurs Europeens de Motocycles,2010).
Our study included core motorcycle firms(assemblers) that sold products in Italy (regard-less of their country of origin) and peripheralfirms (suppliers) localized in Italy that special-ized in the design and/or manufacture of industrycomponents. Both of these types of firms workwithin a network structure of non-equity, long-term cooperative buyer/supplier relationships. Weselected core firms on the basis of lists sup-plied by the Italian Ministry of Transportation(from www.trasporti.gov.it) and the trade associa-tion (www.ancma.it), and we used Italian marketsales performance figures for 2007, the most recentyear for which comprehensive statistics were avail-able. We contacted representatives at the full list of25 core firms specializing in scooter and/or motor-cycle design and/or production, and 17—coveringnearly 85 percent of Italian market sales—agreedto participate. In selecting peripheral firms, wefirst used business publications to identify relevantgroups of two-wheeler components and modules,each including multiple, often specialized, sub-components (thus, ‘body’ includes frame, suspen-sion, forks, etc.; ‘brakes’ include drums, cylinders,pads, shoes, etc.). Working from publicly avail-able sources (e.g., motorcycle and spare parts cata-logs, national and international exhibition businessdirectories, online bikers’ communities, etc.), weidentified a list of 43 component suppliers. Check-ing this list with our full core firm group, weidentified 19 suppliers who each had links withat least seven core firms: 13 of them agreed toparticipate and supplied details about their ties tocore firms.
Data collection and analyses
To avoid restrictive theoretical or empiricallenses (Santos and Eisenhardt, 2005), we definedknowledge broadly, as encompassing both easilycodifiable and transmittable information and com-plex and more difficult to codify know-how. Theinteraction patterns we noted implied the existenceof ties between two entities, which we define asvoluntary collaborative arrangements of strategicsignificance between independent organizations,based on written contracts and aimed at sharingtacit and explicit knowledge. Our study employed
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 581
several data sources: quantitative and qualitativedata from semi-structured interviews with exec-utives from both tie partners; archival data (pressreleases, annual reports, corporate documents,etc.); direct observations, including visits to theR&D units, plants, and headquarters of nearlyall core firms and every peripheral firm; ande-mails, phone calls, and follow-up interviews. Inparticular, we conducted 81 face-to-face on-siteinterviews (totaling nearly 170 hours) over a28-month period in 2007, 2008, and 2010 with 52different executives from both core and peripheralfirms. Respondents were selected according toseveral criteria (Yin, 1994): long tenure in thecompany; direct involvement in knowledge-relateddecisions; and functional and hierarchical variety.This use of multiple internal sources helpedmitigate the potential biases of any individualrespondent (Kumar, Stern, and Anderson, 1993).3
We began our interviews at the core firms.Each consisted of three main parts: backgroundinformation on the firm and its business strategy;description of key events in the formation andevolution of the firm’s ties (if any) with our samplesuppliers; and direct questions about knowledgeexchange/creation, including details of develop-ment projects for new scooter/motorcycle com-ponents core firms had with each listed supplier.The first interview round (2007 to 2008) focusedon projects from 2004 to 2007, and the secondround (2010) focused on 2008 to 2009 projects. Wequeried the types of knowledge exchanged witheach supplier and the main direction of knowl-edge flows, which might be simple—mostly out-bound flows of information and know-how towardsuppliers or return flows to core firms—or moreadvanced—bidirectional and intertwined interac-tions that might contribute to the cogeneration ofknowledge. Lastly, we asked core firms about thepractices they had implemented to support suchknowledge flows and any that facilitated flowsbetween their suppliers. We used interview tech-niques such as ‘event tracking’ to gain accurateinformation (Eisenhardt, 1989) and repeated theprocess later with peripheral firms. We triangulatedour interview data with observation and archivaldata to improve its accuracy and completeness,combining contemporary and retrospective data
3 The composition of our sample firms, their product ranges, andthe position of each company’s interviewees is available onlineSee Appendix S1.
to improve both external and internal validity(Leonard-Barton, 1990).
We selected key peripheral firm informants onthe same criteria as for core firms and followedthe same basic interview structure so that theresponses complemented our core firm data. Weasked supplier executives to report about the spe-cific projects identified by the core firms—aboutthe levels of relevant information and know-howthey had received from their buyers, the knowl-edge they had returned to them embedded incomponents or services, and about bidirectionalflows and joint knowledge creation. They alsoreported on knowledge flows between them andother peripheral firms promoted by a commoncore firm. In all, we collected data on 892 projectsenacted via 184 dyads connecting 17 core firmsand 13 peripheral firms: more specifically, on776 projects carried out via 163 buyer–supplierties and 116 stemming from 21 supplier-supplierrelationships. All these collaborations (58 ofwhich involved racing) were based on writtencontracts and (as our interview analysis revealed)could be categorized into one of three broad func-tional areas: R&D, operations, and other up- anddownstream activities, which we identified as theindustry’s focal organizational areas for knowledgeexchange and creation. Figure 1 highlights thewhole pattern of ties between core and peripheralfirms (solid lines), as well as between peripheralfirms (dotted lines). Table 1 highlights the mainactivities carried out by the core firms and thecomponents/groups supplied by peripheral firms.
Our data analyses were structured accordingto established procedures for theory buildingfrom inductive research, working recursivelybetween multiple cases and theory (Eisenhardt,1989; Yin, 1994). We included all the interviewsand archival and observational data in a reportof approximately 550 pages (including quotes),beginning with in-depth analyses, synthesizingthe data for each project and dyad into individualcase histories, and noting knowledge flows, theirdominant directions, and the practices underlyingthem. We then moved to cross-case analyses,which produced consistent patterns and commonthemes (Eisenhardt and Graebner, 2007): initiallywe compared varied pairs of cases (e.g., specificknowledge transfer occurrences seen from thecore and peripheral firms’ perspectives) and addedother interfirm knowledge-enhancing practicesas patterns emerge to identify more robust
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
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582 A. Lipparini, G. Lorenzoni, and S. Ferriani
P13P2
P1
nb=7ns=3
nb=14ns=4
P12 P3
P11P4
P5
P10
P9 P6
P8 P7
= tie between core firms and peripheral firms= tie between peripheral firms
nb = number of ties with core firmsns = number of ties with other peripheral firms
nb=9ns=3
nb=17ns=7
nb=11ns=5
nb=13ns=4
nb=16ns=4
nb=12ns=3
nb=10ns=5
nb=9ns=0
nb=16ns=0
nb=13ns=0
nb=16ns=4
YamahaAprilia
Betamotor
CagivaSuzuki
BMW
MV Agusta
Piaggio
Moto Guzzi
Mbk
Malaguti KymcoKTM
H-D
Honda
Ducati
Husqvarna
Figure 1. Ties between Italian top two-wheeler buyers (or ‘core firms’) and key component suppliers(or ‘peripheral firms’ - P). N = 184.
causal and temporal relationships (Eisenhardt,1989).
We structured our analysis of knowledge-enhancing practices using a ‘temporal bracketing’strategy (Langley, 1999), organizing the data intosuccessive ‘phases,’ defined so that there is con-tinuity in the activities within each phase but dis-continuities at their frontiers (Langley and Truax,1994). As Langley (1999: 703) notes, ‘many tem-poral processes can be decomposed in this way,at least partly, without presuming any progressivedevelopmental logic.’ Our data analysis allowed usto develop a four-phase conceptual model of howcore firms deliberately shaped knowledge prac-tices to stimulate interfirm knowledge exchangeand creation, at both the dyad and network levels.Our firm informants helped us identify and validatethe four phases and the knowledge flows involved.
THE SHAPING OF KNOWLEDGEEXCHANGE AND CREATION IN DYADSAND NETWORK: A FOUR-PHASEMODEL
The interfirm exchange and co-creation of knowl-edge in the Italian motorcycle industry network weinvestigated can be portrayed in four phases. InPhase 1, knowledge flows are mainly from core toperipheral firm, the former channeling informationand know-how to a number of selected suppliers.In Phase 2, knowledge flows reverse this direc-tion, moving mainly to core firms from peripherals,who return some of the knowledge they origi-nally received in more refined forms and transferssome of their own proprietary knowledge to thecore firms. Once knowledge transfer channels havebeen established, Phase 3 sees bidirectional flows,
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 583
Table 1. Core and peripheral firms (activities andcomponents/groups supplied)
Core firms Activities
Aprilia Scooter and motorcycle design andproduction
Betamotor Motorcycle design and productionBMW Motorcycle design and productionCagiva Motorcycle design and productionDucati Motorcycle design and productionHarley-Davidson Motorcycle design and productionHonda Motor Scooter and motorcycle design and
productionHusqvarna Motorcycle design and productionKTM Motorcycle design and productionKymco Scooter design and productionMalaguti Scooter design and productionMBK Scooter design and productionMoto Guzzi Motorcycle design and productionMV Agusta Scooter design and productionPiaggio Motorcycle design and productionSuzuki Scooter and motorcycle design and
productionYamaha Scooter and motorcycle design and
production
Peripheral firms Specialized components/groups
P1 Electronic ignition and batteryrecharging system
P2 Electronic carburetors/oil pumps/throttle bodies
P3 BrakesP4 WheelsP5 Steel and light alloy precision
frameworksP6 Forks - shock absorbersP7 Front suspensionsP8 Shock absorbers - fuel pumps and valvesP9 Plastic - rubberP10 Turn indicators - lightsP11 Tail lights - indicators - reflectorsP12 Light alloy cast components and
integral wheelsP13 Design and development
with core and peripheral firms exchanging knowl-edge simultaneously, making it difficult to identifya predominant direction. In Phase 4, knowledgeflows between peripheral firms that are linked tothe same core firm, and learning extends fromdyads to the network.
These phases do not represent ‘stages’ in thesense of being a predictable and sequential processand do not imply a progressive life cycle logic asfound in many normative change theories. Specifi-cally, they allow us to constitute comparative units
of analysis to explore theoretical ideas (Langley,1999)—and are especially useful in illustratinghow the actions in one period affect those under-taken in the next. Figure 2 illustrates the temporalstructuring of the different phases, showing how anexample core firm (Honda Italia) maintains a port-folio of ties with different peripheral firms. Eachcore firm will have such a portfolio of ongoingprojects with each supplier, which may be at differ-ent phases and may relate to R&D, operations, orupstream/downstream activities alone, or to themall. This example case shows Honda’s portfolio ofeight projects (related to the many versions of itsscooters and bikes) in which it collaborates withP12 (a steel alloy body supplier) and their differentlearning phases. Thus, Project A (the heavyweightCBR1000RR bike entirely designed and manufac-tured in Italy) entered Phase 1 in Q1, 2003 andPhase 2 in Q2, 2004, and has been in Phase 3since Q2, 2006. Project B (developing and manu-facturing frames for top-selling scooters, e.g., theSH300) spent more than two years in Phase 1, hadbeen through Phase 2 (with inbound flows overlap-ping the Phase 1 outbound flows by a considerablemargin), and entered Phase 3 in Q1, 2009. At thetime of the survey, it was expected to enter Phase4 in Q2, 2012, as the peripheral firm P12 startscollaborations with two other suppliers to developa frame for next-generation scooters. Project C(developing steel alloy frame for scooters like theForesight 250) has been in Phase 1 since Q1,2003: Honda Japan had already developed defini-tive engineering details, and suppliers were invitedto exploit Honda’s innovation to add value forboth partners. But Phase 4-type information andknow-how flows have been taking place betweenthe frame maker and partners supplying brakingsystems and wheels (three highly interdependentcomponents) since Q2, 2008. At the time of thesurvey, Project C was expected to enter Phase 2in Q3, 2012, with inbound knowledge flows fromP12 constituting the platform for Honda engineers’future design activities.
Phase 1—Knowledge flows from core firms toperipheral firms
Core firms are channeling knowledge (informationand know-how) to peripheral firms in differentforms and at different codification levels, leadingto spiraling interactions between tacit and explicitknowledge (Nonaka, 1994). Table 2 reports some
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
584 A. Lipparini, G. Lorenzoni, and S. Ferriani
Q1-2003 PHASE1Q4-2004
Q2-2006Overlapping ofknowledge flows
CBR1000RR
Q2-2004PHASE
2
PHASE3
Q4-2006
Overlapping ofknowledge flows
Pro
ject
A
Peri
pher
al f
irm
(P1
2)
PHASE1
PHASE2
Q1-2006Q3-2008
Q1-2007Q2-2009
SH300iPro
ject
B
PHASE3
Q1-2009
ExpectedQ2-2012
Overlapping ofknowledge flows
Overlapping ofknowledge flows PHASE
4
PHASE1
Q1-2003
Q2-2008
PHASE2
Pro
ject
C
Foresight250
PHASE4
Overlapping ofknowledge flows
ExpectedQ3-2012
Figure 2. Example of knowledge flows between core firm (Honda Italia) and peripheral firm (P12-steel alloy framesfor bikes and scooters).
practices that shape outbound flows and the mainbenefits (peripheral) recipients perceive from thoseflows. With respect to R&D (Table 2, Phase 1), in301 projects, we found core firms sharing infor-mation about development cycles with periph-eral firms to ease prototype development andgain time/cost efficiencies. Core firms transferredinformation and techniques on product conceptsand assembly designs to suppliers in nearly one-third of the projects we studied, and they also(to a lesser extent) shared detailed blueprintsand offered specific training about product con-cepts and design-for-assembly logics and tech-niques. Other core firm practices we observedincluded: preparing manuals outlining practicesand rules for R&D interactions, supporting pur-chasing costs of R&D tools, and licensing pro-prietary technologies to peripheral firms. Trans-ferring tacit knowledge effectively requires exten-sive personal contact and trust and the supplier
developing codification processes to transform itinto explicit knowledge. At the operations level(Table 3, Phase 1), practices supporting outboundknowledge flows included: sharing detailed pro-duction schedules with suppliers, checkup visits totheir company and plant, organizing and deliveringtraining about production methods and workingpractices (such as just-in-time and lean productionprinciples) to align and synchronize manufacturingand assembly processes. Core firms also arrangedtraining on statistical quality control methods andquality performance indicators to assist suppli-ers with quality assurance and quality certifica-tion, as well as on ICT and enterprise resourceplanning (ERP) platforms, inventory managementtechniques, and plant management principles. Anumber of practices covered other upstream anddownstream activities (Table 4, Phase 1). Forinstance, core firms revealed proprietary informa-tion about market forecasts and trends to their
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© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 585
Tabl
e2.
The
know
ledg
eflo
ws-
enha
ncin
gpr
actic
esre
late
dto
R&
D.
N=
776
for
Phas
es1,
2,an
d3;
N=
116
for
Phas
e4
%on
%on
Phas
e1
Prac
tices
aim
edat
shap
ing
know
ledg
eflo
ws
Nto
tal
proj
.in
Mai
nbe
nefit
s(a
spe
rcei
ved
bype
riph
eral
firm
s)*
from
core
firm
sto
peri
pher
alfir
ms
proj
ects
Phas
e1
(N=
776)
(N=
362)
Shar
ing
ofin
form
atio
non
deve
lopm
ent
cycl
es30
138
.883
.1C
ost
and
time
savi
ngs
-pr
oces
ssy
nchr
oniz
atio
nT
rans
fer
ofin
form
atio
nan
dte
chni
ques
onpr
oduc
tco
ncep
tan
dde
sign
for
asse
mbl
y26
333
.972
.7K
now
ledg
etr
ansf
eref
fect
iven
ess
-pr
oces
sim
prov
emen
tsSh
arin
gof
deta
iled
blue
prin
ts20
926
.957
.7Q
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prov
emen
t-
time
savi
ngs
Spec
ific
trai
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ign
(or
real
ign)
reci
proc
alR
&D
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824
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.9Im
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166
21.4
45.9
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inte
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Supp
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sing
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lignm
ent
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crea
sed
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sing
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etar
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chno
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119
15.3
32.9
Incr
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-re
duce
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*fr
ompe
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sto
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spr
ojec
tsPh
ase
2(N
=77
6)(N
=21
3)
Tra
nsfe
rof
spec
ializ
edkn
owle
dge
and
tech
nica
lin
form
atio
non
stat
e-of
-the
-art
tech
nolo
gy
176
22.7
82.6
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lity
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ent
-ef
fect
iven
ess
ofkn
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tran
sfer
Com
pone
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odul
ede
sign
-in
activ
ities
169
21.8
79.3
Alig
nmen
tw
ithbu
yers
’pr
oduc
tar
chite
ctur
e-
cost
adva
ntag
eSh
arin
gof
prop
riet
ary
tech
nolo
gyan
dkn
ow-h
ow14
318
.467
.1Sa
tisfy
cust
omer
s’de
man
dof
uniq
uene
ss-
unle
ash
know
ledg
epo
tent
ial
Inte
rnal
trai
ning
tode
velo
pde
sign
-sha
ring
capa
bilit
ies
140
18.0
65.7
Impr
ove
the
eval
uatio
nof
desi
gnal
tern
ativ
es-
time
savi
ngs
Use
ofra
pid
prot
otyp
ing
tech
niqu
es12
315
.957
.7C
ost
redu
ctio
n-
time
savi
ngs
Sim
ulat
ion-
driv
ende
sign
/Off
-the
-she
lfm
echa
nica
lsi
mul
atio
nso
ftw
are
112
14.4
52.6
Red
uctio
nof
engi
neer
ing
cost
s-
mor
eef
fect
ive
desi
gnan
alys
esD
evel
opm
ent
ofun
ique
tech
nica
lso
lutio
nsfo
rra
cing
activ
ities
9111
.742
.7E
nabl
ing
the
tech
nolo
gy’s
pote
ntia
l-
lear
ning
byra
cing
effe
cts
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
586 A. Lipparini, G. Lorenzoni, and S. Ferriani
Tabl
e2.
Con
tinue
d
%on
%on
Phas
e3
Prac
tices
aim
edat
shap
ing
bidi
rect
iona
lkn
owle
dge
Nto
tal
proj
.in
Mai
nbe
nefit
s(a
spe
rcei
ved
bypa
rtie
sin
ady
ad)*
flow
s(b
etw
een
core
and
peri
pher
alfir
ms)
proj
ects
Phas
e3
(N=
776)
(N=
201)
Stru
ctur
edm
eetin
gson
aw
eekl
yba
sis
143
18.4
71.1
Iden
tifica
tion
ofho
wto
fixpr
oble
ms
-fa
stre
spon
seIm
plem
enta
tion
ofco
mpo
nent
san
dm
odul
esco
desi
gnan
dco
-eng
inee
ring
activ
ities
132
17.0
65.7
Cos
tre
duct
ion
-tim
esa
ving
s
Gue
sten
gine
ers
atth
ecu
stom
er’s
and
the
supp
lier’
spl
ant
116
14.9
57.7
Shar
ing
ofca
pab.
inco
ncur
rent
deve
lop.
-le
arni
ngfr
omot
hers
Join
tte
sts
ona
regu
lar
basi
s11
514
.857
.2Q
ualit
yim
prov
emen
t-
impr
oved
relia
bilit
yJo
int
trai
ning
onva
lue
engi
neer
ing/
valu
ean
alys
isac
tiviti
es98
12.6
48.8
Unl
eash
edte
chno
logy
’spo
tent
ial
-tim
esa
ving
sR
egul
arco
nfro
ntat
ion
onho
wto
sync
hron
ize
and
upda
teC
AD
mod
els
9412
.146
.8U
pdat
ing
ofto
ols
-tim
esa
ving
s
Buy
er–
supp
lier
tria
lce
nter
sfo
rra
cing
expe
rien
ces
658.
432
.3Sh
apin
gof
know
ledg
ead
vanc
emen
ts-
fast
resp
onse
%on
Phas
e4
Prac
tices
aim
edat
shap
ing
know
ledg
eN
tota
lPo
tent
ial
bene
fits
(exp
ecte
dby
core
firm
s)*
flow
sbe
twee
npe
riph
eral
firm
spr
ojec
ts(N
=11
6)
Tra
inin
gpr
ovid
edby
core
firm
sto
impr
ove
first
-tie
rsu
pplie
rs’
team
-wor
king
skill
s69
59.5
-D
evel
opm
ent
ofre
latio
nal
capa
bilit
ies
-hi
gher
effe
ctiv
enes
sT
rans
fer
ofm
etho
ds/te
chni
ques
tost
imul
ate
code
sign
activ
ities
amon
gfir
sttie
rs58
50.0
-Sh
arin
gof
prac
tices
-hi
gher
effic
ienc
yan
def
fect
iven
ess
Reg
ular
sem
inar
san
dw
orks
hops
onR
&D
’sor
gani
zing
prin
cipl
esat
the
netw
ork
leve
l36
31.0
-E
ffec
tive
know
.ge
nera
tion,
tran
sfer
,an
dac
cess
-tim
esa
ving
sA
ssis
tanc
ein
the
iden
tifica
tion
ofse
cond
tiers
with
com
plem
enta
ryR
&D
capa
bilit
ies
2925
.0-
Acc
ess
toun
ique
R&
Dca
pabi
litie
s-
netw
ork
effe
ctiv
enes
s
Not
e:D
ots
refe
rto
core
firm
s/bu
yers
(cir
cle)
and
peri
pher
alfir
ms/
supp
liers
(tri
angl
es).
Arr
ows
conn
ectin
gdo
tshi
ghlig
htth
em
ain
dire
ctio
nalit
yof
know
ledg
eflo
ws.
*O
nly
the
two
mos
thi
ghly
cite
dbe
nefit
sfr
omfie
ldin
terv
iew
sar
ere
port
ed.
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 587
Tabl
e3.
The
know
ledg
eflo
ws-
enha
ncin
gpr
actic
esre
late
dto
oper
atio
ns.
N=
776
for
Phas
es1,
2,an
d3;
N=
116
for
Phas
e4.
%on
%on
Phas
e1
Prac
tices
aim
edat
shap
ing
know
ledg
eN
tota
lpr
oj.
inM
ain
bene
fits
(as
perc
eive
dby
peri
pher
alfir
ms)
*flo
ws
from
core
firm
sto
peri
pher
alfir
ms
proj
ects
Phas
e1
(N=
776)
(N=
362)
Shar
ing
ofde
taile
dpr
oduc
tion
sche
dulin
gpr
ogra
ms
324
41.8
89.5
Tim
esa
ving
s-
impr
oved
plan
ning
capa
bilit
ies
Com
pany
and
plan
tvi
sits
for
chec
kup
309
39.8
85.4
Cos
tef
ficie
ncie
s-
fast
reco
very
Tra
inin
gon
prod
uctio
nm
etho
dsan
dw
orki
ngpr
actic
es(e
.g.,
just
-in-
time
and
lean
prod
uctio
n)25
432
.770
.2C
ost
and
time
savi
ngs
-in
crea
sed
prod
uctiv
ity
Con
sulta
ncy
rela
ted
toqu
ality
assu
ranc
e19
625
.354
.1H
igh
relia
bilit
y-
cost
savi
ngs
Tra
inin
gre
late
dto
ICT
and
ER
Ppl
atfo
rms
168
21.6
46.4
Tim
eef
ficie
ncie
s-
impr
oved
com
mun
icat
ion
Supp
ort
prov
ided
for
qual
ityce
rtifi
catio
n15
620
.143
.1H
igh
relia
bilit
y-
impa
cton
supp
liers
’re
puta
tion
Tech
nica
lsu
ppor
tin
buyi
ngeq
uipm
ent/m
achi
nery
132
17.0
36.5
Cos
tsa
ving
s-
high
relia
bilit
yat
the
proc
ess
leve
lT
rain
ing
onin
vent
ory
man
agem
ent
tech
niqu
esan
dpr
inci
ples
ofpl
ant
man
agem
ent
127
16.4
35.1
Cos
tef
ficie
ncie
s-
was
tere
duct
ions
%on
%on
Phas
e2
Prac
tices
aim
edat
shap
ing
know
ledg
eflo
ws
from
Nto
tal
proj
.in
Mai
nbe
nefit
s(a
spe
rcei
ved
byco
refir
ms)
*pe
riph
eral
firm
sto
core
firm
spr
ojec
tsPh
ase
2(N
=77
6)(N
=21
3)
Inve
stm
ent
onhi
ghly
spec
ializ
edfin
ishi
ngpr
oces
ses
and
trea
tmen
t16
421
.177
.0H
igh
qual
ity-
cost
savi
ngs
Del
iver
ing
ofup
date
dpr
oduc
tion
sche
dulin
gpr
ogra
ms
147
18.9
69.0
Qui
ckra
mp-
upto
requ
ired
outp
utle
vel
-hi
ghfle
xibi
lity
Inve
stm
ent
onth
ede
velo
pmen
tof
prod
uctio
nqu
ality
capa
bilit
ies
121
15.6
56.8
Aug
men
ted
prod
uctiv
ityan
dqu
ality
-co
stsa
ving
sPr
even
tive
mai
nten
ance
ofth
em
achi
nes
118
15.2
55.4
Cos
tan
dtim
esa
ving
s-
high
qual
ityD
edic
ated
tool
man
ufac
turi
ng/C
NC
mac
hine
s/C
AD
-CA
Mst
atio
ns/fl
exib
lem
fg.
stat
ions
109
14.0
51.2
Flex
ibili
tyan
dre
liabi
lity
-tim
ean
dco
stef
ficie
ncy
Hom
olog
atio
ntr
ials
rela
tive
topr
oduc
tssu
pplie
dby
the
cust
omer
9712
.545
.5H
igh
qual
ity-
relia
bilit
y
Stat
ic/d
ynam
icpr
oduc
tlia
bilit
yan
dm
ater
ial
com
posi
tion
test
sin
the
man
yst
ages
ofpr
oduc
tion
9612
.445
.1H
igh
conf
orm
ityan
dqu
ality
-in
crea
sed
prod
uct
dura
bilit
yIn
vest
men
tin
robo
tized
wor
kun
its/la
ser
cutti
ngst
atio
ns/d
ie-c
astin
gfo
undr
y83
10.7
39.0
Tim
eef
ficie
ncy
-qu
ality
impr
ovem
ents
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
588 A. Lipparini, G. Lorenzoni, and S. Ferriani
Tabl
e3.
Con
tinue
d
%on
%on
Phas
e3
Prac
tices
aim
edat
shap
ing
bidi
rect
iona
lkn
owle
dge
Nto
tal
proj
.in
Mai
nbe
nefit
s(a
spe
rcei
ved
bybo
thpa
rtie
sin
ady
ad)*
flow
s(b
etw
een
core
and
peri
pher
alfir
ms)
proj
ects
Phas
e3
(N=
776)
(N=
201)
Mon
thly
mee
tings
for
aco
nsta
ntas
sess
men
tof
the
pull
logi
c(i
nre
spon
seto
dem
and)
155
20.0
77.1
Alig
nmen
t-
low
erco
ordi
natio
nco
sts
Join
tas
sess
men
tof
prin
cipl
esan
dte
chni
ques
ofle
anm
anuf
actu
ring
and
valu
est
ream
map
ping
143
18.4
71.1
Hig
hef
ficie
ncy
ofco
stan
dtim
e-
disc
over
yof
oppo
rtun
ities
Join
top
timiz
atio
nof
war
ehou
sest
ock
volu
mes
,jo
int
orde
rsfo
rpu
rcha
sing
mat
eria
ls12
816
.563
.7C
ost
savi
ngs
-re
duct
ion
ofop
port
unity
cost
s
Join
tin
vest
men
tfo
rth
eim
plem
enta
tion
ofin
tegr
ated
ente
rpri
sere
sour
cepl
anni
ng(E
RP)
122
15.7
60.7
Sche
dulin
gan
dm
onito
ring
ofpr
oduc
tion
-hi
ghef
ficie
ncy
Act
ivat
ion
ofqu
ality
circ
les
tore
duce
defe
cts,
scra
ps,
and
was
te10
113
.050
.2C
ost
savi
ngs
-de
velo
pmen
tof
reco
very
capa
bilit
ies
Join
tin
itiat
ives
for
fast
erde
liver
yof
spar
epa
rts,
impr
ovin
gth
equ
ality
ofre
pair
ing
serv
ices
9011
.644
.8T
ime
effic
ienc
y-
impa
cton
repu
tatio
n
Con
stan
tco
nfro
ntat
ion
onst
atis
tical
qual
ityco
ntro
lm
etho
dsan
dqu
ality
perf
orm
ance
indi
cato
rs85
11.0
42.3
Cos
tsa
ving
s-
high
conf
orm
ity
Initi
ativ
esto
supp
ort
the
full
inte
grat
ion
oflo
gist
icpr
oces
ses
ofbo
thpa
rtie
s85
11.0
42.3
Cos
tan
dtim
eef
ficie
ncy
-fa
stre
spon
ses
%on
Phas
e4
Prac
tices
aim
edat
shap
ing
know
ledg
eflo
ws
betw
een
Nto
tal
Pote
ntia
lbe
nefit
s(e
xpec
ted
byco
refir
ms)
*pe
riph
eral
firm
spr
ojec
ts(N
=11
6)
Initi
ativ
es(e
.g.,
wor
ksho
psan
dco
achi
ng)
toex
tend
effe
ctiv
eSC
Man
dm
fg.
prac
tices
toth
ew
hole
netw
ork
4942
.2-
Net
wor
kef
ficie
ncy
and
effe
ctiv
enes
s-
high
prod
uctiv
ity
Tra
nsfe
rof
met
hods
/tech
niqu
esto
stim
ulat
eco
ordi
natio
nof
mfg
.ac
tiviti
esam
ong
first
tiers
3933
.6-
Impr
ovem
ents
ofm
anuf
actu
ring
capa
bilit
ies
-ne
twor
kef
ficie
ncy
Tra
inin
gon
the
diff
usio
nof
plan
ning
tool
s(e
.g.,
soft
war
esy
stem
s)fr
omin
itial
orde
rto
deliv
ery
2723
.3-
Impr
oved
plan
ning
capa
city
-be
tter
plan
tut
iliza
tion
Ass
ista
nce
bybu
yer
firm
sin
the
initi
alst
ages
ofth
eir
rela
tions
hip
with
othe
rsu
pplie
rs22
19.0
-In
crea
sed
netw
orki
ngca
paci
ty-
netw
ork
resp
onsi
vene
ss
Not
e:D
ots
refe
rto
core
firm
s/bu
yers
(cir
cle)
and
peri
pher
alfir
ms/
supp
liers
(tri
angl
es).
Arr
ows
conn
ectin
gdo
tshi
ghlig
htth
em
ain
dire
ctio
nalit
yof
know
ledg
eflo
ws.
*O
nly
the
two
mos
thi
ghly
cite
dbe
nefit
sfr
omfie
ldin
terv
iew
sar
ere
port
ed.
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 589
Tabl
e4.
The
know
ledg
eflo
ws-
enha
ncin
gpr
actic
esre
late
dto
upst
ream
and
dow
nstr
eam
activ
ities
.N
=77
6fo
rPh
ases
1,2,
and
3;N
=11
6fo
rPh
ase
4
%on
%on
Phas
e1
Prac
tices
aim
edat
shap
ing
know
ledg
eflo
ws
Nto
tal
proj
.in
Mai
nbe
nefit
s(a
spe
rcei
ved
bype
riph
eral
firm
s)fr
omco
refir
ms
tope
riph
eral
firm
spr
ojec
tsPh
ase
1(N
=77
6)(N
=36
2)
Man
ager
ial
supp
ort
prov
ided
tosu
pplie
rsfo
rm
arke
tfo
reca
sts
and
mar
ket
tren
ds15
920
.543
.9Im
prov
edpl
anni
ngca
paci
ties
-op
erat
iona
lef
fect
iven
ess
Tra
inin
gon
the
brea
kdow
nof
cost
s(s
ugge
stin
gw
ays
that
supp
liers
can
seek
tore
duce
cost
s)13
317
.136
.7C
ost
savi
ngs
-op
port
uniti
esfo
rne
win
vest
men
tsT
rain
ing
supp
liers
onm
anag
emen
t/str
ateg
yto
ols
insu
ppor
tof
the
dyad
120
15.5
33.1
Acc
urat
ese
izin
gof
mar
kets
-as
sess
men
tof
reso
urce
sFi
nanc
ial
supp
ort
toth
esu
pplie
r’s
proc
urem
ent
ofto
ols
and
equi
pmen
t11
815
.232
.6C
ost
effic
ienc
ies
-op
port
uniti
esfo
rne
win
vest
men
tsC
omm
unic
atio
nin
itiat
ive
infa
vor
tosu
pplie
rsto
enla
rge
thei
rsp
are
mar
ket
109
14.0
30.1
Bet
ter
asse
ssm
ent
ofm
arke
ts-
addi
tiona
lre
sour
ces
Priv
ilege
dac
cess
tore
sour
ces
(e.g
.,ta
lent
edem
ploy
ees)
via
bene
fit-r
ich
ties
102
13.1
28.2
Impr
oved
capa
bilit
yba
se-
acce
ssto
dist
inct
ive
capa
b.Su
ppor
tin
the
prep
arat
ion
ofan
expo
rtpl
ans
(for
thos
esu
pplie
rsw
how
ant
toex
port
over
seas
)98
12.6
27.1
Stra
tegi
cef
fect
iven
ess
-im
prov
edm
anag
eria
lfo
resi
ght
Tra
inin
gon
mar
ketin
gan
dre
latio
nal
capa
bilit
ies
toen
larg
eth
esu
pplie
r’s
cust
omer
base
8511
.023
.5R
educ
edde
pend
ence
byco
refir
ms
-le
arni
ngfr
omot
hers
%on
%on
Phas
e2
Prac
tices
aim
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ledg
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Nto
tal
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Mai
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spe
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ved
byco
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ms)
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riph
eral
firm
sto
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firm
spr
ojec
tsPh
ase
2(N
=77
6)(N
=21
3)
Det
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dbr
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own
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and
tran
spar
ency
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eva
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131
16.9
61.5
Impr
oved
capa
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inva
lue
anal
ysis
-tr
ust
cons
olid
atio
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ppor
tin
the
prep
arat
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ofte
chni
cal
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ifica
tions
and
docu
men
tsfo
rfin
alus
ers
129
16.6
60.6
Incr
ease
dre
liabi
lity
-im
pact
onco
refir
m’s
imag
eSh
arin
gof
info
rmat
ion
rela
tives
toco
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emen
tary
sour
ces
ofco
mpo
nent
san
dte
chno
logy
105
13.5
49.3
Effi
cien
cyin
crea
ses
-as
sesm
ent
ofsu
pply
mar
kets
Seiz
ing
oppo
rtun
ities
tocu
stom
ers
(e.g
.,lo
wer
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sion
san
dre
spec
tof
regu
latio
ns)
9812
.646
.0H
igh
relia
bilit
y-
dist
inct
posi
tioni
ngon
final
mar
ket
Del
iber
ate
tran
sfer
of’l
earn
ing
from
othe
rs’
rela
ted
toth
epo
rtfo
lioof
ties
inth
ein
dust
ry93
12.0
43.7
Impo
rtof
best
prac
tices
-cr
oss-
fert
iliza
tion
Sugg
estio
nsfo
rth
em
aste
ring
ofth
ebu
yer’
sbu
sine
ssca
pabi
litie
s79
10.2
37.1
Cap
abili
tyim
prov
emen
ts-
new
busi
ness
oppo
rtun
ities
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
590 A. Lipparini, G. Lorenzoni, and S. Ferriani
Tabl
e4.
Con
tinue
d
%on
%on
Phas
e3
Prac
tices
aim
edat
shap
ing
bidi
rect
iona
lkn
owle
dge
Nto
tal
proj
.in
Mai
nbe
nefit
s(a
spe
rcei
ved
bybo
thpa
rtie
sin
ady
ad)*
flow
s(b
etw
een
core
and
peri
pher
alfir
ms)
proj
ects
Phas
e3
(N=
776)
(N=
201)
Join
tas
sess
men
tof
end
user
profi
les
109
14.0
54.2
Cus
tom
ized
resp
onse
s-
impa
cton
com
petit
ive
posi
tioni
ngJo
int
part
icip
atio
nin
proj
ects
for
fund
-rai
sing
101
13.0
50.2
Res
ourc
eav
aila
bilit
y-
oppo
rtun
ities
disc
over
yPe
riod
ical
chec
ksfo
ref
ficie
ncy
inin
terfi
rmco
mm
unic
atio
nan
dtr
ansf
erof
info
rmat
ion
9612
.447
.8E
ffici
ent
know
ledg
etr
ansf
er-
effe
ctiv
ere
cove
ryJo
int
eval
uatio
nof
chan
ges
inbu
sine
ssm
odel
s(e
.g.,
selli
ngth
roug
hth
eIn
tern
et)
9111
.745
.3N
ewbu
sine
ssop
port
uniti
es-
sens
ing
ofm
arke
top
port
.Jo
int
rela
tions
with
core
rese
arch
inst
itutio
nsan
dot
her
rele
vant
acto
rs58
7.5
28.9
New
busi
ness
oppo
rtun
ities
-ca
pabi
lity
deve
lopm
ent
Defi
nitio
nof
coor
dina
ted
resp
onse
sto
oppo
rtun
istic
beha
vior
sfr
ompa
rtne
rsin
the
netw
ork
435.
521
.4R
educ
tion
ofth
reat
sof
know
.le
akin
g-
netw
ork
iden
tity
%on
Phas
e4
Prac
tices
aim
edat
shap
ing
know
ledg
eflo
ws
betw
een
Nto
tal
Pote
ntia
lbe
nefit
s(e
xpec
ted
byco
refir
ms)
*pe
riph
eral
firm
spr
ojec
ts(N
=11
6)
Org
aniz
atio
nof
conf
ront
atio
nal
sess
ions
amon
gfir
st
tiers
onm
arke
tfo
reca
sts
5446
.6-
Eff
ectiv
enes
s-
impr
oved
asse
ssm
ent
capa
city
Bra
inst
orm
ing
sess
ions
for
the
join
tid
entifi
catio
nof
syne
rgie
sac
ross
diff
eren
tal
lianc
es51
44.0
-C
apab
ility
deve
lopm
ent
-di
scov
erin
gof
oppo
rtun
ities
Stru
ctur
ing
and
man
agem
ent
ofjo
int
arch
ives
onpo
tent
ial
part
ners
orle
sson
sle
arne
d47
40.5
-T
ime
effic
ienc
y-
oppo
rtun
itycr
eatio
n
Coa
chin
gse
ssio
nsw
ithfir
sttie
rsin
volv
edin
com
mon
proj
ects
tore
info
rce
colla
bora
tive
cultu
re32
27.6
-N
etw
ork
effe
ctiv
enes
s-
netw
ork
adap
tabi
lity
Spon
sori
ngev
ents
with
first
tiers
supp
liers
for
goal
sal
ignm
ent
and
cont
inuo
usim
prov
emen
t29
25.0
-N
etw
ork
effe
ctiv
enes
s-
incr
ease
dse
nse
ofco
mm
unity
Ass
ista
nce
inth
ede
finiti
onan
dim
plem
enta
tion
of‘n
etw
ork
cont
ract
’(r
ecen
tlyin
trod
uced
inth
eIt
alia
nle
gisl
ativ
efr
amew
ork)
2622
.4-
Net
wor
kid
entit
y-
effe
ctiv
ere
spon
ses
Not
e:D
ots
refe
rto
core
firm
s/bu
yers
(cir
cle)
and
peri
pher
alfir
ms/
supp
liers
(tri
angl
es).
Arr
ows
conn
ectin
gdo
tshi
ghlig
htth
em
ain
dire
ctio
nalit
yof
know
ledg
eflo
ws.
*O
nly
the
two
mos
thi
ghly
cite
dbe
nefit
sfr
omfie
ldin
terv
iew
sar
ere
port
ed.
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 591
peripheral firms, thus improving their planningcapacities and operational effectiveness, and alsogave training on cost breakdowns and on manage-ment and strategy tools to help suppliers improvetheir efficiency, even providing financial supportto help them buy tools and equipment. Core firmsalso established communication initiatives aimedat helping suppliers find new markets to increasetheir abilities to identify and enter new markets(often related to racing events) to help improvetheir financial stability: shaping joint visions andseizing market opportunities allowed these part-ners to develop joint dynamic capabilities.
Phase 2—Knowledge flows from peripheralfirms to core firms
Peripheral firms relying simply on markets toaccess specialized assets and acquire technologyare likely to see their capabilities deteriorate(Teece, 1986) and to remain stuck in passive,dependent postures (Rosenberg, 1982). Periph-erals that purposefully supply core firms withreturn knowledge turn their relationships intopartnerships, making it harder for core firms toswitch to other suppliers. In terms of inboundR&D knowledge (Table 2, Phase 2), our studydepicts peripheral firms as providing special-ized knowledge and technical information: bysharing proprietary technology and know-how,including alerting their partners about advances instate-of-the-art technologies and proposing designalternatives to allow them to fulfill their customers’unique demands more completely. Other practicesincluded: organizing training sessions to developdesign-sharing capabilities, developing rapid pro-totyping techniques, and using simulation-drivendesign to give core partners with significant engi-neering cost benefits and more effective designanalysis. At the operations level (Table 3, Phase2), suppliers shaped their knowledge flows to corefirms by investing in highly specialized finishingprocesses and treatments, a practice we observedin nearly one-fifth of the projects and which bene-fitted a wide range of activities including productand process feasibility, surfacing, structural anal-ysis, and prototype engineering. Peripheral firmsalso transferred knowledge embedded in updatedproduction scheduling programs, made consider-able investments in developing quality productioncapabilities, and offered preventive maintenanceof core firms’ production machinery—flows that
were enabled by their possession of dedicatedmanufacturing tools, CNC machines, CAD-CAMworking stations, and flexible manufacturing sys-tems. Such inbound flows also extended to otherupstream and downstream activities (Table 4,Phase 2). Peripheral firms provided core firmswith detailed price breakdowns and supportedthe preparation of technical specifications anddocuments for final users, building core firms’reliability and reputation. Their practices extendedto sharing information about complementarysources of components and technology, whichmay seem to be counterintuitive behavior, butwas aimed at reinforcing network potential andeffectiveness and supporting core firms’ reactionsto market opportunities, e.g., by speedy responseto changing vehicle emissions regulations.
Phase 3—Simultaneous, bidirectionalknowledge flows between core and peripheralfirms
In Phase 3, firms reciprocally exchange knowledgeand cocreate ‘collaborative knowledge’ (Simonin,1997), a prerequisite for virtuous relational learn-ing. In terms of R&D at this phase (Table 2,Phase 3), design engineers on both sides of thedyads recognized the value of working together onprojects to share expertise, foster problem solving,and improve the efficiency and quality of prod-uct development: the interaction inherent in theseknowledge-enhancing practices nourished virtu-ous cycles of reciprocal learning. In the projectswe studied, we observed structured meetings toexchange information and know-how to fix prob-lems rapidly, as well as recurrent codesign andco-engineering activities at component and mod-ule levels, joint testing, and the systematic paral-lel updating of partners’ CAD models to reducedesign times and costs, allowing both parties torapidly assess concept, development, and total leadtimes via interfirm ties. Hosting partners’ engi-neering teams supported simultaneous knowledgeexchanges, and our data also revealed a signif-icant number of relational platforms (or ‘cus-tomer trial centers,’ as one core company labeledthem) where teams of engineers from core andperipheral firms interacted to solve specific prob-lems. Joint participation in racing also enhancedboth parties’ knowledge and supported their R&Dactivities, as many innovations developed for rac-ing bikes were later featured in retail production
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
592 A. Lipparini, G. Lorenzoni, and S. Ferriani
models. At the operations level (Table 3, Phase 3),monthly meetings were arranged in one-fifth of theprojects we studied, allowing them to constantlyassess the ‘pull’ logic, increasing core/peripheryalignment and time efficiency and lowering coordi-nation costs. We also noted how parties interactedto jointly assess lean manufacturing principles andtechniques and employed value stream mappingto raise their cost and time efficiency and theireffectiveness in attaining manufacturing goals.Other practices supporting bidirectional knowl-edge flows included: synchronizing purchasingorders and optimizing warehouse stock volumes,jointly implementing integrated enterprise resourceplanning (ERP), and using ‘quality circle’ initia-tives to cut defects and waste. In the ‘other activ-ities’ sphere (Table 4, Phase 3), we saw evidenceof joint assessment of end user profiles to improveresponse effectiveness and participation in fund-raising projects to increase resource availability.Coevolutionary alignment took the form of theperiodic updating of communication and informa-tion flows needed to respond quickly to environ-mental jolts or to competitors’ moves.
Phase 4—Knowledge flows between peripheralfirms
In the fourth model phase, we observed knowl-edge flowing between different peripheral firms,whose connection had been promoted and sup-ported by a common core firm. Largely unexploredby strategic literature, this guided evolution oflearning processes from dyads to networks yieldssignificant insight into how core firms connectalters to gain informational (Burt, 2000) and otherdifficult-to-replicate network-specific advantages.Redeploying knowledge dispersed across collabo-rative networks requires that core firms possess (ordevelop) learning and teaching capabilities acrossorganizational boundaries, as this targeted coordi-nation of knowledge mobility is central to a net-work’s ability to co-create value and innovation(Zhao et al., 2005). As for R&D (Table 2, Phase4), we observed knowledge exchange and cre-ation between peripheral firms being accomplishedby: training suppliers on improving team workingskills for greater effectiveness across dyads andnetworks, transferring methods and techniques tostimulate co-design activities among first-tier sup-pliers, and organizing workshops and seminars onR&D organizing principles at the network level.
Core firms supported such intersupplier knowledgeflows by identifying second-tier suppliers withcomplementary R&D capabilities. At the opera-tions level (Table 3, Phase 4), core firms extendedeffective supply chain and manufacturing activitiesacross their networks by organizing workshops andcoaching sessions, transferring methods and tech-niques to stimulate coordination among first-tiersuppliers, and providing training to diffuse plan-ning tools covering a range of activities from initialorders to delivery. To a lesser extent, we also sawcore firms play active roles in helping peripheralsmanage the initial stages of their interrelationships,such as helping develop joint manufacturing plans.In other areas (Table 4, Phase 4), core firms orga-nized sessions between peripheral firms on marketforecasts and identified synergies across differ-ent alliances. Core firms’ ability to lead by shar-ing strategy also hinged on them sharing lessonslearned, databases, and potential partner profilesto create further opportunities for their suppli-ers. Core firms ran coaching sessions to reinforcethe network’s goal alignment and helped supplierselaborate ‘network contracts’ to give them uniqueidentities in fund-raising applications.4
DISCUSSION AND CONCLUSION
We present a structured framework that takes amultilevel perspective to address different rela-tional subsets, depicting knowledge flows at dyadand network levels. We found core firms thattook charge of the processes of interfirm learn-ing from firms to dyads, and from dyads to net-works, and of knowledge-enhancing practices allneeded to nurture the transfer, recombination andcreation of specialized knowledge. Such practicesare favoring the affirmation of higher-order orga-nizing principles (Grant, 1996), the idiosyncraticlearning processes (Kotabe et al., 2003), and theinterfirm knowledge-sharing routines (Dyer andSingh, 1998). The network we studied combinedthe advantages of common identity and lan-guage normally associated with hierarchical forms(Kogut and Zander, 1992; Conner and Prahalad,1996) with the learning incentives that typicallyoccur in dyads and networks. Having multiple
4 Key quotes from our interviews across the four phases areavailable online See Appendix S2.
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
© 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.
Research Notes and Commentaries 593
actors involved in defining the rules governingcooperation decisions (Kogut, 2000) led the net-work to develop stronger shared identity and lan-guage, lowering the costs of communication andknowledge exchange, establishing rules and prin-ciples for coordination, and influencing the direc-tion(s) of both searching and learning. The wholenetwork, thus, becomes more expert at captur-ing opportunities, developing new products, andextracting technical and organizational capabili-ties both from current ties and from dormant orunexpected contacts (Kane, 2010). In our setting,the threat of opportunism appears to have beenmore than outweighed by the advantages of: learn-ing from other partners (Lorenzoni and Lipparini,1999), including developing joint ‘interaction rou-tines’ (Nelson and Winter, 1982), making iteasier for firms to modify existing behaviorpatterns as needed and improving transactiveknowledge—about who knows what—to betterenable information transfer (Reagans, Argote, andBrooks, 2005). These incentives help firms per-ceive networks as ‘safe places’ where ideas andknowledge can be exchanged, but with reducedrisk of knowledge spillovers to competitors whoshare the same partners (Lester and Piore, 2004).
Our findings suggest that all else being equal,the most successful learning processes will accruein dyads and networks where both sources andrecipients possess the requisite knowledge trans-fer capacity. A company’s capacity to effectivelydeploy knowledge is only as strong as the weakestpartner in its innovation value chain, so unilat-eral flows of knowledge to third parties do notguarantee the sustainability of any advantage. Wecontribute to explaining why some dyads and net-works succeed in learning faster than their com-petitors (Dyer and Nobeoka, 2000), enabling theirpartner firms to achieve their strategic objectives(Zollo, Reuer, and Singh, 2002). Our study alsocontributes to clarifying the role of firm capabil-ities in alliances and, in particular, the capabil-ities they need when entering alliances. Extantcontributions have carefully examined alliance(Kale, Dyer, and Singh, 2002), relational (Loren-zoni and Lipparini, 1999) or boundary-bridging(Takeishi, 2001) and orchestration capabilities(Dhanaraj and Parkhe, 2006), and we add tothis list the capacity for transferring and creat-ing knowledge (Smith, Collins, and Clark, 2005)which we show is needed by all parties indyads and networks. Future research could refine
and build on this study in several directions:it could empirically determine which networkstructure dimensions are most likely to influ-ence project outcomes, as well as examine therelationship between project phases, knowledge-enhancing activities, and outcomes. Equally inter-esting would be to study whether informal, distant,or infrequent relationships—rather than strongrecurring ties among a small number of buyers andsuppliers—lead to more or less efficient knowl-edge sharing (Hansen et al., 2005). It would alsobe interesting to consider ‘negative ties’ (Labiancaand Brass, 2006), given that many of the corefirms in our sample are competitors. As to this, itcould be interesting to examine how competitiverelationships between core firms might influence,for instance, choices about forming ties with spe-cific peripheral firms that are already tied to rivals(Gimeno, 2004), therefore gaining a deeper under-standing of both the ‘structure of cooperation’(Ahuja, 2000) and the structure of competition.
ACKNOWLEDGEMENTS
We received valuable insights from Will Mitchelland from two anonymous reviewers. We thankJon Morgan of Paraphrase for expert copyeditingand Lois Gast for effective management of thismanuscript. We express our appreciation to allthe firms, respondents, and interviewees whoparticipated in this study. We acknowledge supportfrom the Strategy & Organization Center at theUniversity of Bologna. The authors alone areresponsible for errors and omissions.
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SUPPORTING INFORMATION
Additional supporting information may be foundin the online version of this article:
Appendix S1. List of core and peripheral firms(product mix and company’s interviewees)Appendix S2. Typical quotes illustrating patternsof interaction in the Italian motorcycle industry(excerpts from the interviews)
Strat. Mgmt. J., 35: 578–595 (2014)DOI: 10.1002/smj
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