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