Social Capital and the

Creation of Knowledge

Claudia Gonzalez-BrambilaFrancisco VelosoDavid Krackhardt

INFORMS, November 2006

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Outline

Introduction Objective The data Importance The models Results Conclusions

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Introduction

“Social capital metaphor is that people who do better are

somehow better connected”

Critical question is what is social capital?– Coleman (1988): Actors in embedded networks have

superior achievements » Members obtain more coordination, they trust each other and

develop better communication skills. – Burt (1992): Actors in open social structures with many

structural holes, do better» Members can take advantage of “bridges” to connect with new

members in other clusters, and get access to new information

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Introduction

Growing importance of production, dissemination and use of knowledge

Little understanding of what determines how such crucial knowledge is created

The interaction between individuals plays a critical role – social capital

Growing attention to the role of collaborative effort in the process of scientific knowledge generation

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Objectives

Paper examines the relationship between social capital and knowledge creation– Knowledge creation is research output and

impact in the area of Natural Sciences–Creation process measured using publications

and citations in ISI – Web of Science–Social capital is measured through co-

authorship

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The Data

Data from SNI – National System of Researchers in Mexico

Information on 1,704 researchers in Natural Sciences that have been part of the SNI from 1991 to 2002

Information on all their publications in ISI Web of Science from 1981 to 2002–Publications per year–Citations per year –Authors per publication

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Importance

Study enables analysis of most critical aspects of social capital: –Embeddedness –Positioning–Network Structure

Considers panel data with entire network

Study outside developed world - Mexico

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Critical Aspects of Social Capital

Relational dimension:– Direct ties– Strengths of direct ties

Structural dimension– Density– Structural holes– Centrality– External-Internal index in terms of fields of knowledge

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The Models Dependent variables:

– Number of publications– Number of cites in the subsequent 4 years

Methods: –Negative Binomial fixed effects

Pit = F (Xit-1, ci, uit)– Xit-1: varies in both dimensions

» number of direct ties, strength of direct ties, structural holes, density, normalized eigenvector (centrality), external-internal index,

» Controls – past reputation and output, time– ci: individual unobserved effect– uit: error– Times: t-> 2 years; t-1 -> 3 years

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Some Results

*** significant at 0.1%, ** significant at 1%, * significant at 5%

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Conclusions

Factors of social capital that consistently enhance productivity and impact:– Number of direct ties– Non dense networks

Influence output productivity, not impact– Centrality– Collaboration with researchers in other disciplines

Influence impact but not output productivity– Strenght of Direct ties

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Conclusions

The structural holes variable is not significant when other variables are included–This variable has been used as the main

measure of social capital

It is critical to control for various dimensions of social capital, as well as for unobserved individual heterogeneity

Questions, Comments, Suggestions

Thank you