Presentation on theme: "Social Times of Network Spaces David Stark and Balazs Vedres."— Presentation 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 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 1December, 1987
Month 2January, 1988
Month 3February, 1988
Month 4March, 1988
Month 5April, 1988
Month 6May, 1988
Month 7June, 1988
Month 8July, 1988
Month 9August, 1988
Month 10September, 1988
Month 11October, 1988
Month 12November, 1988
Month 13December, 1988
Month 14January, 1989
Month 15February, 1989
Month 16March, 1989
Month 17April, 1989
Month 18May, 1989
Month 19June, 1989
Month 20July, 1989
Month 21August, 1989
Month 22September, 1989
Month 23October, 1989
Month 24November, 1989
Month 25December, 1989
Month 26January, 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
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.
Industry Agriculture ** 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) ** Early foreign ownership (1990) 4.326** Constant.205**-.935** N … LL … …. R-squared Percentage correctly classified 66.7… …... χ 2 (df) (11) (28) p-value.000…
Hungary is not a segregated dual economy Globalization is compatible with local embeddings Forms 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.