evolution of the strategic alliance network in the global information sector david knoke & xi...
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Evolution of the Strategic Alliance Network in the Global Information Sector David Knoke & Xi Zhu University of Minnesota SIENA Workshop Groningen University January 8-11, 2007. - PowerPoint PPT PresentationTRANSCRIPT
Thanks to the Ford Foundation, Digital Media Forum, and University of Minnesota for funding and to Anne Genereux, Song Yang, and Francisco J. Granadosfor research assistance.
Evolution of the Strategic Alliance Network in the Global Information Sector
David Knoke & Xi Zhu
University of Minnesota
SIENA Workshop
Groningen University
January 8-11, 2007
Corporate Social Capital
Corporate Social Capital (CSC) Social relations embedded in work-related organizational roles (e.g., workers, teams, executives, owners), not in their personal networks.
“Corporate social capital, then, refers to: The set of resources, tangible or virtual, that accrue to a corporate player through the player’s social relationships, facilitating the attainment of goals.” (Leenders & Gabbay 1999:3)
Social Capital Resources accruing to an ego actor through direct and indirect relations with its alters that facilitate ego’s attainment of its expressive or instrumental goals.
“inheres in the structure of relations between persons and among persons” (Coleman 1990:302) “at once the resources contacts hold and the structure of contacts in the network” (Burt 1992:12) “resources embedded in a social structure which are accessed and/or mobilized in purposive action” (Lin 2001:12)
Diverse conceptualizations of an actor’s social capital:
CSC through SANs
A firm’s ties to organizations in a strategic alliance network increases its probability of accessing and using the valuable CSC resources held by the firm’s partners, including their:
Organizations aware of such CSC advantages may act strategically in pursuing new alliances, partnering with firms that maximize its CSC portfolio. At the field-net level, an evolving strategic alliance network comprises a collective CSC structure which simultaneously facilitates and constrains the opportunities for its member firms.
Financial resources, credit extensions
Knowledge, information, technologies/patents
Marketing expertise, country/culture penetration
Org’l statuses, corporate/brand reputations
Trustworthiness and low risk (moral hazards)
Strategic Alliance Networks
Corporate social capital relations span multiple levels of analysis from individuals, to workteams, to firms, and organizational field network (Kenis & Knoke 2002). At the IOR level, repeated alliances generate a strategic alliance network form of CSC.
Strategic alliance network “The set of organizations connected through their overlapping partnerships in different strategic alliances” (Knoke 2001:128; Todeva & Knoke 2002). Firms are closely tied to one another through many direct alliances or many indirect ties through third firms (i.e., partners-of-partners).
Strategic alliance: at least two partner firms that (1) remain legally independent; (2) share benefits, managerial control over performance of assigned tasks; (3) make contributions in strategic areas, e.g., technology or products (Yoshino & Rangan 1995).
Global Information SectorBasic CSC concepts could help to explain the evolution of the strategic alliance network in the Global Information Sector (GIS). This sector increased collaborative agreements exponentially 1989-2000, creating a complex web of overlapping partnerships.
Five NAICS info subsectors (publishing; motion pictures & sound recording; broadcasting & telecomms; info services & data processing) plus computer, telecomm, semiconductor manufacturing industries
145 multinational corporations: 66% USA, 16% Europe, 15% Asia
Alliance & venture announcements in general & business news media from 1989 to 2000
Total of 3,569 alliances involving two or more GIS organizations (some alliances include noncore partners)
Research HypothesesThree types of H’s about network evolution involve changes in global structure, partner choice, and organizational performances.
H1: Network Structural Change: The GIS SAN evolved from a fragmented small world of specialized cliques toward preferential attachments to key producers, and then to structurally cohesive connectivity.
H2a: Transitivity: Firms are more likely to form new alliances with other organizations that result in transitivity.
H2b: Balance: Firms with a specific number of partners are more likely to form new alliances with other orgs having an identical or very similar N of partners.
H2c: Indirect Relations: Firms are more likely to form new alliances with other organizations to which they are linked by numerous indirect connections.
H2d: Similarity / Interdependence: Firms are more likely to form new alliances with other organizations that having similar / complementary attributes.
Rising Alliance Rates
GIS Strategic Alliances 1989-2000
YEAR
2000199819961994199219901988
FR
EQ
UE
NC
Y
5
4
3
2
1
0
Total (100s)
Mean per Org
Diverse Purposes
GIS Types of Alliances
YEAR
2000199819961994199219901988
PE
RC
EN
T o
f A
LL
IAN
CE
S
100
90
80
70
60
50
40
30
20
10
0
Equity Investment
Product Adaptation
Research & Develop
Marketing
Production
Contract
L icense
Standards
Legal-Political
Closeness Centrality
GIS Closeness 1989-2000
Y EAR
2000199819961994199219901988
CL
OS
EN
ES
S
6.0
5.0
4.0
3.0
2.0
1.0
0.0
Network
Mean
CLOSENESS
1991: AT&T
1995: IBM; Sun; Intel
2000: Microsoft; IBM; Sun; HP
CENTRALITY: ORGS INVOLVED WITH MANY PARTNERSDEGREE = Number of ties directly connecting focal org to other orgs (in- or out-degrees)
CLOSENESS = Inverse of sum of distances to other orgs (geodesics = shortest paths)
NETWORK CENTRALIZATION: Extent to which one actor has high centrality and others low
Betweenness Centrality
GIS Betweenness 1989-2000
Y EAR
2000199819961994199219901988
BE
TW
EE
NN
ES
S
100.0
80.0
60.0
40.0
20.0
0.0
Network
Mean
BETWEENESS
1991: AT&T; Time Warner
1995: AT&T; Intel; IBM
2000: Microsoft; IBM
CENTRALITY: ORGS INVOLVED WITH MANY PARTNERSBETWEENNESS = Number of times an org occurs on a geodesic between other pairs of orgs
NETWORK CENTRALIZATION: Extent to which one actor has high centrality and others low
MAPPING The GIS COREHierarchical cluster & multidimensional scaling analyses
to identify positions and spatial proximities among 30 most-active GIS firms (1991, 1995, 2000).
Similarity = N of partnerships per dyad.
Organization Primary SIC
America Online AOL Info retrieval
Apple Computer
AT&T Telecomm
BellSouth BS Telecomm
Cisco Communic equip
Compaq Computer
Hewlett-Packard HP Computer
IBM Computer
Intel Semiconductor
Microsoft Software
Motorola TV equip
Novell Software
Oracle Software
Sun Microsystems Computer
Texas Instruments TI Semiconductor
Organization Primary SIC
British Telecomm BT Telecomm
Ericsson Telecomm equip
France Telecomm FT Telecomm
Philips TV equip
Siemens Computer periph
Fujitsu Computer
Hitachi Computer
Matsushita AV equip
Mitsubishi AV equip
NEC Computer
NTT Telecomm
Sony AV equip
Toshiba AV equip
Bell Canada BCE Telecomm
Samsung (Korea) Semiconductor
GIS Core Alliances in the Triad
J apan-Europe
Europe-USA
USA-J apan
Europe
J apan
USA
ME
AN
AL
LIA
NC
ES
6
5
4
3
2
1
0
Y R91
Y R95
Y R00
1991 GIS (MDS Stress = 0.102)
1.5.5-.5-1.5
1.0
0.0
-1.0
TOSHIBA
TI
SUN
SONY
SIEMENS
PHILIPS
ORACLE
NTT
NOVELLNEC
MOTOROLAMITSUBISHI
MICROSOFT
MATSUSHITA
INTEL
IBM
HP
HITACHI
FUJITSU
FT
ERICSSON
COMPAQ
CISCO
BT
BS
BCE
ATT
APPLE
SAMSUNG
1995 GIS (MDS stress = 0.142)
1.81.51.31.0.8.5.3.0-.3-.5-.8-1.0-1.3-1.5-1.8-2.0-2.3
1.5
1.0
.5
0.0
-.5
-1.0
-1.5
TOSHIBA
TI
SUN
SONY
SIEMENS
SAMSUNG
PHILIPS
ORACLE
NTT
NOVELL
NEC
MOTOROLA
MITSUBISHI
MICROSOFT
MATSUSHITA
INTEL
IBM
HPHITACHI
FUJITSU
FT
ERICSSON
COMPAQ
CISCOBT
BS
BCE
ATT
APPLEAOL
2000 GIS (MDS stress = 0.137)
2.01.51.0.50.0-.5-1.0-1.5-2.0
2.0
1.5
1.0
.5
0.0
-.5
-1.0
-1.5
TOSHIBA
TI
SUN
SONY
SIEMENSSAMSUNG
PHILIPS
ORACLE
NTT
NOVELL
NEC
MOTOROLA
MITSUBISHI
MICROSOFTMATSUSHITA
INTEL
IBM
HP
HITACHI
FUJITSU
FT
ERICSSON
COMPAQ
CISCO
BT
BS
BCE
ATT
APPLE
AOL
Evolution AnalysisThe macro-evolution of GIS alliance network, under dynamic constraints of network properties, assumes methodological individualism (actor-oriented model)
SIENA (Simulation Investigation for Empirical Network Analysis; Snijders 2005) models the changing network connections as outcomes of org’l decisions to add or drop ties, assuming that orgs seek to maximize various “objective function” elements
(e.g., preferences for increased network transitivity, reciprocity, balance, alliances with popular and active partners, etc.)
SIENA estimates effects using two or more observed matrices of dichotomous ties. It applies the method of moments, implemented as a continuous-time Markov chain Monte Carlo simulation (MCMC) [i.e., actors know network’s current structure, but not its earlier states].
GIS Core Firm AlliancesSANs among 26 GIS firms 1998-99-00 (binarized at 2+ per year).
Here is the 2000 matrix, density = 0.618:
Evolution of the GIS CoreSIENA analysis of strategic alliances (dichotomized at 2+ per year)
among the 26 most-active GIS firms for 1998-1999-2000.
Results consistent with all H2’s except transitivity hypothesis.
*p < .05 ** p < .01 ***p < .001
OBJECTIVEFUNCTION Parameter Stnd error t-ratio
Rate (1998-1999) 11.82 2.67 4.43***
Rate (1999-2000) 8.41 1.95 4.31***
Density (degree) 0.71 0.12 5.92***
Transitivity 0.01 0.07 0.14
Balance 1.34 0.31 4.32***
Indirect Relations 0.69 0.19 3.63***
Geographic Similarity 0.47 0.13 3.62***
Industry Similarity 0.21 0.19 1.11
Issues in SAN Evolution
♠ What substantive interpretations can we make about the SIENA parameters? How robust for the larger GIS network and longer evolutionary span?
♦ Which, if any, tie-formation processes in interorganizational relations are functionally equivalent to interpersonal choices?
♥ Do balance and transitivity have the same meanings in organizational partnering and social psychological affiliation?
♣ Are different theoretical concepts, principles, and propositions necessary to explain interorganizational network dynamics? If so, what are they?
Further StepsGIS orgs built up extensive corporate social capital by rapidly expanding the worldwide strategic alliance network. Structural cohesion seems increasing important for collective actions and individual firm outcomes.
By expanding the GIS dataset to cover 1986-2005, I hope to track transformations in structures and processes from the Sector’s origins to well beyond the bursting of the Dot.com Bubble in Spring 2000.
Using data on firm profits, growth, patent innovations, I will test the third set of hypothesis about organizational performance: Are structurally equivalent or socially cohesive clusters of collaborating organizations better able to use the structural advantages of jointly occupied network positions to access valuable information, obtain scarce resources, and improve their members’ performances?
By helping to provide policymakers with a deeper understanding of the types of alliance networks that affect firm innovations, subsequently modified legislative, regulatory, and trade association policies might be crafted to foster the development of interorganizational connections with optimal structural characteristics.
Burt, Ronald S. 1992. Structural Holes: The Social Structure of Competition. Cambridge, MA: Harvard University Press.
Coleman, James S. 1990. “Social Capital.” Pp. 300-321 in Foundations of Social Theory. Cambridge, MA: Harvard University Press.
Kenis, Patrick and David Knoke. 2002. “How Organizational Field Networks Shape Interorganizational Tie-Formation Rates.” Academy of Management Review 27:275-293.
Knoke, David. 2001. Changing Organizations: Business Networks in the New Political Economy. Boulder, CO: Westview.
Leenders, Roger Th. A. J. and Shaul M. Gabbay (eds.). 1999. Corporate Social Capital and Liability. Boston: Kluwer Academic Publishers.
Lin, Nan. 2001. Social Capital: A Theory of Social Structure and Action. New York: Cambridge University Press.
Snijders, Tom A.B. 2005. “Models for Longitudinal Network Data.” Pp. 215-247 in Models and Methods in Social Network Analysis, edited by Peter J. Carrington, John Scott and Stanley Wasserman. New York: Cambridge University Press.
Todeva, Emanuela and David Knoke. 2002. “Strategische Allianzen und Sozialkapital von Unternehmen.” (“Strategic Alliances and Corporate Social Capital”) Kölner Zeitschrift für Sociologie und Sozialpsychologie. Sonderheft 42:345-380.
Yoshino, Michael Y. and U. Srinivasa Rangan. 1995. Strategic Alliances: An Entrepreneurial Approach to Globalization. Cambridge, MA: Harvard University Press.
References