Oslo Summer School in Comparative Social Science Studies 2015

Knowledge, Innovation and Networks in Today’s Economy

Lecturer: Professor Robin Cowan,
Faculty of Economics and Management,
University of Strasbourg, France;
and UNU-MERIT, Maastricht University,
The Netherlands

Main disciplines: Innovation Studies,
Sociology, Economics

Dates: 27 - 31 July 2015
Course Credits: 10 pts (ECTS)
Limitation: 25 participants

For 60 years we have known that innovation, broadly defined, is the main driver of economic growth and development. Innovation can be seen as the act of creating and employing new knowledge or using existing knowledge in a new way. Thus a fundamental issue in understanding how economies grow, develop, evolve, lies in understanding the creation and use of knowledge. These issues have captured attention in many places and at many levels. Academics have changed their views in recent decades about how knowledge, and thus innovation, functions as an economic good. This is seen in studies of technological choice, technology diffusion, intellectual property rights, communities of practice, open innovation and many others. Firms are struggling to compete in a fast-moving, global economy and attempt to do so with innovation. But at the same time the nature of the firm has changed, as innovating often demands access to knowledge or technology not mastered or owned by a single firm: firms attempt to create or cope with “distributed innovation”.

Policy makers fear what will happen if their “local” (often meaning “European”) firms become less competitive as globalization continues to march on, and firms in other parts of the world develop new technologies, products or processes, as competitive firms are seen as central to increasing social welfare. But for firms to innovate they must have access to knowledge, skills, technology and so on. This has brought policy makers to view innovation in terms of an “innovation system” in which different parts of the system act and interact, jointly producing changes in knowledge, technology, hopefully competitiveness, and thus welfare.

Against this backdrop, this course uses social network analysis as a tool for examining these issues. We are concerned both with how networks form, and how they perform. The course will introduce students to recent changes in our understanding of the role of knowledge and how it functions in the modern economy.  Using this as a base, our interest will be largely in how network analysis is useful in understanding innovation and knowledge creation and diffusion. As such we see (social) networks as the infrastructure over which knowledge flows. We seek to understand how different actors in an innovation system interact, and how those interactions can be analyzed with network tools and concepts. We begin with a general introduction to social network analysis, laying out the basic concepts.

The bulk of the course uses these concepts to look at various issues of innovation and development in today’s economy. We look at different network structures and how they might be good or bad for encouraging innovation; we look at models of network formation, starting with the basic building block of links between pairs of actors. The course presents both theoretical and empirical results. Finally, in the last sessions we will examine a variety of empirical applications of network analysis relevant t todays economy and society. Which types of applications precisely will be determined by the interests of the students in the class.

Essential books
Participants must obtain and read this book in advance of the course.

  • Barabasi, A.L. (2002) Linked: The New Science of Networks, Perseus, Cambridge, MA. 

Course topics

  • Knowledge in economics and in the economy
  • An overview of social networks
  • Small worlds and scale free networks (or why (some) physicists are as not smart as they think they are)
  • Centrality, performance and social capital Network architecture and aggregate performance
  • Network architecture and aggregate performance
  • Network Formation
  • Empirical applications in economics and sociology (topics will be tailored to the interests of the students)


1: Knowledge in economics and in the economy

  • Cowan, R. “Network models of innovation and knowledge diffusion” in Clusters, Networks and Innovation, S. Breschi and F. Malerba (eds.) Oxford University Press: Oxford, pp. 29-53, 2005. Available also as a MERIT working paper. Only the first half is necessary at this point.
  • Vega-Redondo, F. (2007) Complex Social Networks  “Chapter 1: Introduction”
  • Kirman, A. 1992.  “Whom or what does the representative agent represent?” Journal of Economic Perspectives vol 6(2), pp. 117-136.
  • C. A. Hidalgo,  B. Klinger, A.-L. Barabási, R. Hausman (2007) “The Product Space Conditions the Development of Nations”  Science 317: 482 – 487  DOI: 10.1126/science.1144581
  • Supplementary material at http://www.nd.edu/~networks/productspace/index.htm

2: An overview of social networks

  • Borgatti, S.P. and Foster, P. 2003. The network paradigm in organizational research:  A review and typology. Journal of Management. 29(6): 991-1013 [pdf]
  • Cross, R., Parker, A., & Borgatti, S.P. 2002. Making Invisible Work Visible: Using Social Network Analysis to Support Strategic Collaboration. California Management Review. 44(2): 25-46. [pdf]
  • Gulati, R. 1998. Alliances and Networks. Strategic Management Journal. 19 293-317.
  • Gulati, R., M. Garguilo 1999. Where do interorganizational networks come from? American Journal of Sociology. 104(5) 1439-93.

3. Small worlds and scale free networks (or why (some) physicists are as not smart as they think they are)

  • Watts and Strogatz, 1998, “Collective dynamics of “small-world” networks, Nature, Jun 4, 393 (6684), 440-2.
  • Baum, JAC , AV Shipilov, TJ Rowley 2003. “Where do small worlds come from?” Industrial and Corporate Change, Volume 12, Number 4, pp. 697-725.
  • Barabási, A.-L. and R. Albert (1999): “Emergence of scaling in random networks,” Science 286, 509-12.
  • Barabasi, A.L. (2002) Linked: The New Science of Networks (Perseus, Cambridge, MA. selected chapters.
  • Kleinberg, J. “The Small-World Phenomenon and Decentralized Search”. A short essay as part of Math Awareness Month 2004, SIAM News 37(3), 2004.
  • Stumpf, M.P.H and M.A Porter (2012) “Critical truths about power laws” Science 335, 665 . DOI: 10.1126/science.1216142
  • Aaron Clauset, Cosma Rohilla Shalizi,  and M. E. J. Newman (2009) “Power-Law Distributions in Empirical Data”  SIAM REVIEW Vol. 51, No. 4, pp. 661–703 (see Three-toed Sloth web log, June 15, 2007)

4. Centrality, performance and social capital

  • Freeman, L. (1979). Centrality in social networks: Conceptual clarification. Social Networks. 1, 215-239.
  • Bonacich, Phillip. 1987. Power and Centrality: A Family of Measures. American Journal of Sociology 92: 1170-1182.
  • Powell, Koput, Smith-Doer and Owen-Smith “ Network Position and Firm Performance: Organizational Returns to Collaboration in the Biotechnology Industry” www.stanford.edu/~woodyp/Rso1.pdf published in Research in the Sociology of Organizations 16:129–59, 1999.          
  • Ahuja, G. 2000. Collaboration Networks, structural holes, and innovation: A longitudinal study.  Administrative Science Quarterly. 45 425-455.
  • Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78:1360-1380
  • Walker, G., B. Kogut, W. Shan. 1997.  Social capital, structural holes and the formation of an industry network. Organization Science. 8(2) 109-125.
  • Guimerà, Roger , Brian Uzzi, Jarrett Spiro, and Luís A. Nunes Amaral,  “Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance” Science 29 April 2005: Vol. 308. no. 5722, pp. 697 - 702

5. Network architecture and aggregate performance

  • Cowan, Robin and Nicolas Jonard, “Structural Holes, Innovation and the Distribution of Ideas” vol (2), pp 93-101, Journal of Economics of Interaction and Co-ordination, DOI: 10.1007/s11403-007-0024-0, 2007.
  • Cowan, Robin and Nicolas Jonard, “Network Structure and the Diffusion of Knowledge” Journal of Economic Dynamics and Control, 28(8) pp. 1557-1575, 2004.
  • Cowan, Robin and Nicolas Jonard “The Dynamics of Collective Invention”, Journal of Economic Behavior and Organization, vol 52(4) pp. 513-532, 2003.
  • Wilhite, A. 2001. Bilateral Trade and ‘Small-World’ Networks, Computational Economics Volume 18, Number 1 / August, 2001 DOI: 10.1023/A:1013814511151 Pages 49-64

6. Network Formation

  • Mowery, D.C. J. Oxley and B. S. Silverman (1998) “Technological Overlap and Interfirm Cooperation: Implications for the Resource-Based View of the Firm”, Research Policy; 27 (5) Pages: 507-523
  • Mowery, D.C. J. Oxley and B. S. Silverman (1996) “Strategic Alliances and Interfirm Knowledge Transfer” Strategic Management Journal, 17(S2) pp. 77-91.
  • Gulati, “Social structure and alliance formation: A longitudinal analysis”, Administrative Science Quarterly, 1995.
  • Baum, J., R. Cowan and N. Jonard(2010), “Network-independent partner selection and the evolution of innovation networks”, Management Science 56: 2094-2110.
  • Powell, Koput, White, Owen-Smith  “Network dynamics and field evolution: The growth of interorganizational collaboration in the life sciences” American Journal of Sociology, 110, 1132-1205, 2005.

7. Empirical applications in economics and sociology
The topics here have a bias towards development. This will be expanded before the course begins in order to tailor topics covered to the interests of the students.

  • Albert, R., H. Jeong, and A.-L. Barabási (1999): “Diameter of the worldwide web,” Nature 401, 130-131.
  • Angelucci, M., G. De Giorgi, M. Rangel, and I. Rasul (2010): “Family Networks and School Enrollment: Evidence from a Randomized Social Experiment”, Journal of Public Economics, 94(3-4),
  • Bandiera, O., and I. Rasul (2006): “Social Networks and Technology Adoption in Northern Mozambique”, Economic Journal, 116(514), pp. 862-902.
  • Banerjee, Abhijit , Arun G. Chandrasekhar, Esther Duflo, Matthew O. Jackson “The Diffusion of Microfinance” Science 341, 1236498 (2013). DOI: 10.1126/science.1236498
  • Barr, Abigail. 2000. “Social Capital and Technical Information Flows in the Ghanaian Manufacturing Sector.” Oxford Economic Papers 52(3):539-59.
  • Calvó-Armengol, A. (2004): “Job contact networks,” Journal of Economic Theory 115, 191-206.
  • Calvó-Armengol, A. and M. O. Jackson (2004): “The effects of social networks on employment and inequality,” American Economic Review 94, 426-454.
  • Calvó-Armengol, A. and Y. Zenou (2004): “Social networks and crime decisions: the role of social structure in facilitating delinquent behavior,” International Economic Review 45, 939-958.
  • Castilla, E. J., H. Hwang, E. Granovetter, and M. Granovetter (2000): “Social Networks in Silicon Valley,” in C.-M. Lee, W. F. Miller, M. G. Hancock, and H. S. Rowen, editors, The Silicon Valley Edge, Stanford: Stanford University Press.
  • Conley, Timothy & Christopher Udry. 2001. “Social Learning through Networks: The Adoption of New Agricultural Technologies in Ghana.” American Journal of Agricultural Economics vol. 83(3) pp. 668-73.
  • Conley, T.G. and C.R Udry, 2010. “Learning about a New Technology: Pineapple in Ghana”, American Economic Review, 100:1, 35-6.
  • Eagle, N., M. Macy and R. Claxton (2010) “Network diversity and develoment” Science, Vol 328, 2 May, pp 1029-1031.
  • Fafchamps, M. and Flore Gubert (2007) “Risk Sharing and Network Formation” American Economic Review Papers and Proceedings, 97(2): 75-79, May 2007
  • (long version: "The Formation of Risk-Sharing Networks", in collaboration with Flore Gubert, Journal of Development Economics, 83(2): 326-50, July 2007)
  • Fafchamps, M. and S. Lund (2003): “Risk-sharing networks in rural Philippines,” Journal of Development Economics 71, 261-87.
  • Krishnan, Pramila & Emanuela Sciubba. 2009. “Links and architecture structure in village networks.” The Economic Journal, 119 (April), 917–949.
  • Mckenzie, David and Hillel Rapoport, Network effects and the dynamics of migration and inequality: Theory and evidence from Mexico, Journal of Development Economics, Volume 84, Issue 1, September 2007, Pages 1-24, ISSN 0304-3878, 10.1016/j.jdeveco.2006.11.003.
  • (http://www.sciencedirect.com/science/article/pii/S0304387806001891)
  • Munshi, K. (2003): “Networks in the modern economy: Mexican migrants in the US labor market,” Quarterly Journal of Economics 118, 549-597.
  • Newman, M. E. J. (2001): “The structure of scientific collaboration networks,” Proceedings of the National Academy of Sciences USA 98, 404- 409.
  • Nyblom, Jukka, Steve Borgatti, Juha Roslakka & Mikko A. Salo. 2003. “Statistical Analysis of Network Data:An Application to Diffusion of Innovation.” Social Networks vol. 25 pp.175-95.
  • Opp, K. D. and C. Gern (1993): “Dissident groups, personal networks, and spontaneous cooperation: the East German revolution of 1989,” American Sociological Review 58, 659-680.
  • Price, D. J. de S. (1965): “Networks of scientific papers,” Science 149, 510-515.
  • Redner, S. (1998): “How popular is your paper? An empirical study of the citation distribution,” European Physical Journal B 4, 131-134.
  • Wonodi, B.B., L. Privor-Dumm, M. Aina, A.M. Pate, R. Reis, P. Gadhoke and O.S. Levine (2012) “Using social network analysis to examine the decision-making process on new vaccine introduction in Nigeria”, Health Policy and Planning 2012;27:ii27–ii38 doi:10.1093/heapol/czs037.
  • Woolcock, Michael and Deepa Narayan (2000) “Social Capital: Implications for Development Theory, Research, and Policy, World Bank Research Observer, Vol 15(1) Pp. 225-249.

A Few Papers on Data and Methodology

  • Borgatti, S.P. and Molina, J.L. 2005. Toward ethical guidelines for network research in organizations. Social Networks. 27(2): 107-117 [pdf]
  • Borgatti, S.P. and Molina, J-L. 2003. Ethical and strategic issues in organizational network analysis. Journal of Applied Behavioral Science. 39(3): 337-350. [pdf]
  • UCINET software guide: https://sites.google.com/site/ucinetsoftware/downloads
  • Marsden, P. V. (1990). Network data and measurement. Annual Review of Sociology, 16,435-463.

Relevant software

  • igraph (for R, C, or python)
  • Gephi
  • Wikipedia has an extensive list


The lecturer
Robin Cowan is Professor of the Economics of Technical Change at the  University of Maastricht, and Professor of Management at the Faculty of Economics and Management at the University of Strasbourg.  He began his official affiliation with  UNU-MERIT in 1996 as a Professorial Fellow.  He studied at Queen's  University in Canada and at Stanford University where he received a PhD in  economics and an MA in philosophy.

Robin Cowan was Assistant Professor of  Economics at the University of Western Ontario until 1998. His current  research has includes several topics: the changing economics of knowledge; social networks and innovation; network structure and network performance;  dynamics of consumption and social status; interacting agents models. In the past he has done consulting research for the OECD on the economics of standards, the European Commission on innovation policy, and the National  Renewable Energy Laboratory on technological lock-in and renewable energy  technologies. In 2004 he won one of 15 prestigious Chaires d'Excellence of the Ministry of research and Education in France.

Did you find what you were looking for?
Tags: Sociology, Innovation Studies, Economics, Summer School, PhD, Networks
Published Dec. 15, 2014 2:22 PM - Last modified Aug. 14, 2017 1:09 PM