Abstract
The network analysis of a technological system combines the interindustry transactions with a matrix of sectoral innovative efforts as measured by R&D investment intensity. The matrixes of interindustry transactions of R&D-embodied products (innovations) are weighted matrixes where the interindustry flows measure the intensity of the innovation diffusion. In the past, studies using this approach in innovation studies have transformed weighted matrixes into binary matrixes of zero and one element where the flows less than a selected threshold value were considered to be zero and the flows greater than the threshold value were counted as one. Such matrix transformation leads to the loss of a great deal of information. In the present study, using degree and clustering coefficients for both binary direct as well as weighted direct techno-economic networks of the manufacturing sector of the German economy, we show that the binary directed network analysis is incapable of refined ranking of interindustry innovation transactions. The total degree index based on the weighted network of the German techno-economic system assigns a unique ranking to each sector, and clustering coefficients show that at least 75% of sectors in the network of Germany have two links with the other industries. However, the same indices based on the binary network are incapable of such refined ranking.
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We thank the anonymous referees for their constructive comments on an earlier version of this paper.
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Abdol S. Soofi is professor of economics, School of Business, University of Wisconsin-Platteville. He received his PhD degree from the Department of Economics, University of California, Riverside. In addition to publishing over fifty articles in leading academic journals, Soofi has co-edited three books: The Development of Science and Technology in Iran: Policies and Learning Frameworks, Palgrave-Macmillan, 2017; Science and Innovation in Iran: Development, Progress, and Challenges, Palgrave-Macmillan in 2013, and Modeling and Forecasting Financial Data: Techniques of Nonlinear Dynamics, Kluwer Publishers, 2002. Soofi has co-authored Global Merger Mergers and Acquisitions: Combining Companies across Borders that was published by Business Expert Press in 2014, and the 2nd expanded edition of the book was published in 2018. Soofi is currently serving as the Guest Editor of a special issue of Journal of Science and Technology Policy Management on the national systems of innovation of Iran.
Abdi Mansoureh received PhD in science & technology policy from the Department of Information Technology Management, Tarbiat Modares University, Tehran, Iran. She received her BSc in industrial engineering from Bu Ali Sina University and her MSc in industrial engineering from Tarbiat Modares University. Her thesis is about policy extracting to promote NIS in Iran by theory of constraints.
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Soofi, A.S., Abdi, M. The Social Network Analysis of Techno-Economic Systems: Comparing Results Based on Binary and Weighted Networks. J. Syst. Sci. Syst. Eng. 29, 68–84 (2020). https://doi.org/10.1007/s11518-019-5432-x
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DOI: https://doi.org/10.1007/s11518-019-5432-x