social times of network spaces david stark and balazs vedres
TRANSCRIPT
Social Times of Network Spaces
David Stark and Balazs Vedres
to model, from its inception, network formation across an entire epoch of economic transformation
Processes of network evolution
Embeddedness of foreign capital?
analytic move from how a national economy is integrated into the world economy to whether and how FDI is integrated into local networks
Methodological innovation
We modify analytic tools from DNA sequencing to reconcile the structural focus of social network analysis with the temporal orientation of historical sociology
Structure as topology and temporality
Emergence of domestic networks
Massive decline of state ownership
Extraordinary institutional uncertainty
Ambiguity about the rules of the game
Foreign investment
Did massive FDI eradicate networks?
Which forms were open or closed to FDI?
Do foreigners build domestic networks?
Our question
Can networks of global reach coexist and entwine with those of local embeddedness?
Restated, can FDI be integrated into national networks? And, if so, how?
Data Largest 1,800 firms of the period by revenue between 1987-2001
Ownership data from registry courts
names of top 25 owners and their shares all changes recorded for the whole life of the
firm
A tie is a direct ownership stake by one of our 1,800 firms in one of the other firms in that same population (i.e., not an “affiliation network”)
The ‘network movie’
Animation of network emergence
Month 1 December, 1987
Month 2 January, 1988
Month 3 February, 1988
Month 4 March, 1988
Month 5 April, 1988
Month 6 May, 1988
Month 7 June, 1988
Month 8 July, 1988
Month 9 August, 1988
Month 10 September, 1988
Month 11 October, 1988
Month 12 November, 1988
Month 13 December, 1988
Month 14 January, 1989
Month 15 February, 1989
Month 16 March, 1989
Month 17 April, 1989
Month 18 May, 1989
Month 19 June, 1989
Month 20 July, 1989
Month 21 August, 1989
Month 22 September, 1989
Month 23 October, 1989
Month 24 November, 1989
Month 25 December, 1989
Month 26 January, 1990
[Continues to 169th month ]
For historical network analysis
from a kind of aerial sociology to the network histories of 1,800 firms.
To move from system-level properties to historical processes at the level of firms ...
For historical network analysis Network analysis: topology Historical analysis: temporality Synthesis: find structures in social space and
social times Methodological innovation: Sequence analysis
of network positions to identify pathways through local network topologies
From time as a variable to time as variable
Probe for differences in types of embeddedness Different local network topographic
properties reflect different organizing practices
Firms can use network properties, for example, to hide assets, to restructure assets, to gain access to knowledge, to increase legitimation, to secure access to supplies and markets, and so on
Structure as topology and temporality
Studying variation in the sequences of local structures is a way to identify distinctive pathways of network evolution
1990
1989 1990 1991
7. Member of a strongly cohesive group
6. Member of a cohesive group
5. Star center
4. Large star periphery
3. Small star periphery
2. Dyad component member
1. Isolate
GraphColorName
From 1,696 firm histories we need to find similar sequences. We use optimal matching analysis to find the distance of each sequence from all others.
Finding sequential equivalence
To the resulting matrix we then apply hierarchical clustering that groups sequences so that within-cluster distances are as low as possible and between-cluster distances are high.
The combination of these two algorithms, yields – not unlike the concept of structural equivalence in network analysis – sequential equivalence.
Sizeable foreign ownership
in 2001 (Yes = 1)
model 1
model 2
Star-periphery recombinants
1 (I-S) -5.513** -5.781** 2 (P) -.422** -.785**
Cohesive recombinants
3 (I-P-C-P) -.065** .622** 4 (C-G-C) .485** 1.112** 5 (C-G-I) 1.327** 2.047** 6 (I-L-C-G) -1.091** -1.341**
Startups
7 (P-I) 1.565** 2.087** 8 (D-I) .342** 1.076** 9 (P-D) 1.419** 2.756**
Second wave networks
10 (I-D-P) 1.218** 1.752**11 (D-P) 1.184** 1.717**
Foreign ownership in 2001: Logistic regression estimates
Independent variablesPathways
Industry
Agriculture -2.973** Food 2.779** Energy and mining .996** Chemical 4.756** Heavy industry 1.768** Light industry and textile
.378** Construction -.517** Wholesale .391** Retail 3.695** Finance .359**
Local network position in 2001
D (dyad) -.720** P (small star periphery)
-.097** L (large star periphery)
1.892** S (star center) .140** C (cohesive cluster) -.039** G (strongly cohesive group)
-2.737**Early foreign ownership (1990) 4.326**
Constant .205** -.935**N 1286..….... 1286..…....-2LL 1709.03…. 1326.78….R-squared .249... .498...Percentage correctly classified 66.7…... 74.8…...χ2 (df) 302.45 (11) 684.71 (28)p-value .000… .000…
Hungary is not a segregated dual economyGlobalization is compatible with local
embeddingsForms of recombinant property are robust Cohesive forms are adaptive
An internationalized market economy emerged in Hungary not despite but, instead, because of inter-organizational ownership networks.
Developing economies do not necessarily face a forced choice between networks of global reach and those of local embeddedness.
High levels of foreign investment can be integrated into processes of inter-organizational ownership network formation in a developing economy.