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APPLYING SOCIAL NETWORK ANALYSIS TO INPUT-OUTPUT BASED INNOVATION MATRICES: AN ILLUSTRATIVE APPLICATION TO SIX OECD TECHNOLOGICAL SYSTEMS FOR THE MIDDLE 1990s

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  • Sandro Montresor
  • Giuseppe Vittucci Marzetti

Abstract

The paper discusses, illustrates and possibly contributes to overcoming two methodological problems that emerge in applying Social Network Analysis (SNA) to the study of IO-based innovation flows matrices. The first has to do with the scale-effects these matrices suffer from. The second refers to the need of dichotomising the matrices. Through an illustrative application to six OECD countries in the mid-1990s, the paper shows that, as for the former problem, different relativisation procedures can be, and have been, used, which either tend to alter the actual meaning of standard SNA indicators, or do not properly take into account the actual composition of countries' final demand. As for the latter problem, the paper shows that the choice of discrete cut-offs is extremely sensitive, as comparative results actually change along the continuum of the matrices values. In order to overcome the scale problem, a new relativisation procedure is put forward that measures innovation flows embodied in a unit value basket of final demand and thus properly retains all the information provided by the original matrix of intersectoral innovation (embodied) flows. In addressing the problem of dichotomisation, the paper suggests, as a second best, to work with density distributions that can make the choice of discrete cut-off values less arbitrary.

Suggested Citation

  • Sandro Montresor & Giuseppe Vittucci Marzetti, 2009. "APPLYING SOCIAL NETWORK ANALYSIS TO INPUT-OUTPUT BASED INNOVATION MATRICES: AN ILLUSTRATIVE APPLICATION TO SIX OECD TECHNOLOGICAL SYSTEMS FOR THE MIDDLE 1990s," Economic Systems Research, Taylor & Francis Journals, vol. 21(2), pages 129-149.
    • Handle: RePEc:taf:ecsysr:v:21:y:2009:i:2:p:129-149
    DOI: 10.1080/09535310902940228
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    Citations

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    Cited by:

    1. Taalbi, Josef, 2020. "Evolution and structure of technological systems - An innovation output network," Research Policy, Elsevier, vol. 49(8).
    2. Sailan Hu & Rongrong Li, 2021. "Investigating the Effects of the United States’ Economic Slowdown Related to the COVID-19 Pandemic on Energy Consumption in Other Countries—A Global Vector Autoregressive Model," Energies, MDPI, vol. 14(11), pages 1-25, May.
    3. Fernando DePaolis & Phil Murphy & M. Clara DePaolis Kaluza, 2020. "Identifying Key Sectors in the Regional Economy: A Network Analysis Approach Using Input-Output Data," Papers 2005.11285, arXiv.org, revised Sep 2022.
    4. Fabrizio Fusillo & Sandro Montresor & Giuseppe Vittucci Marzetti, 2021. "The global network of embodied R&D flows," Discussion Paper series in Regional Science & Economic Geography 2021-05, Gran Sasso Science Institute, Social Sciences, revised Apr 2021.
    5. Daria Ciriaci & Sandro Montresor & Daniela Palma, 2013. "Do KIBS make manufacturing more innovative? An empirical investigation for four European countries," JRC Working Papers on Corporate R&D and Innovation 2013-04, Joint Research Centre.
    6. Theodore Tsekeris, 2017. "Network analysis of inter-sectoral relationships and key sectors in the Greek economy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 413-435, July.
    7. Wang, Chengwei & Miao, Wang & Lu, Miaomiao, 2022. "Evolution of the Chinese industrial structure: A social network perspective," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    8. García Muñiz, Ana Salomé & Ramos Carvajal, Carmen, 2012. "Linkages, contagion and resilience: an input-output scope from the demand and supply side," MPRA Paper 59369, University Library of Munich, Germany.
    9. Ana Salome GARCIA MUÑIZ & Carmen RAMOS CARVAJAL, 2015. "Input-Output Linkages And Network Contagion In Greece:Demand And Supply View," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(2), pages 35-52.
    10. Halkos, George & Tsilika, Kyriaki, 2016. "Assessing classical input output structures with trade networks: A graph theory approach," MPRA Paper 72511, University Library of Munich, Germany.
    11. Franco, Chiara & Montresor, Sandro & Vittucci Marzetti, Giuseppe, 2011. "On indirect trade-related R&D spillovers: The "Average Propagation Length" of foreign R&D," Structural Change and Economic Dynamics, Elsevier, vol. 22(3), pages 227-237, September.
    12. George E. Halkos & Kyriaki D. Tsilika, 2018. "A New Vision of Classical Multi-regional Input–Output Models," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 571-594, March.

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