Abstract
This paper analyzed the spreading effect of industrial sectors with complex network model under perspective of econophysics. Input-output analysis, as an important research tool, focuses more on static analysis. However, the fundamental aim of industry analysis is to figure out how interaction between different industries makes impacts on economic development, which turns out to be a dynamic process. Thus, industrial complex network based on input-output tables from WIOD is proposed to be a bridge connecting accurate static quantitative analysis and comparable dynamic one. With application of revised structural holes theory, flow betweenness and random walk centrality were respectively chosen to evaluate industrial sectors’ long-term and short-term spreading effect process in this paper. It shows that industries with higher flow betweenness or random walk centrality would bring about more intensive industrial spreading effect to the industrial chains they stands in, because value stream transmission of industrial sectors depends on how many products or services it can get from the other ones, and they are regarded as brokers with bigger information superiority and more intermediate interests.
Highlights
In last two decades, statistic physics has been wildly adopted in researching on the dynamic and statistic properties embedded in various economic behaviors and data of the global economic infrastructures [1]
According to assumption and formula about CF, each industrial sector’s flow betweenness in ISTN-CHN models was calculated, and the results are in S2 File in details
In ISTN-CHN models, nodes from S4 to S18 represent industrial sectors in secondary industries, in which distinct forward and direct relationships exist among certain adjacent sectors, in other words they respectively locate on upstream and downstream segments in industrial value chain
Summary
Statistic physics has been wildly adopted in researching on the dynamic and statistic properties embedded in various economic behaviors and data of the global economic infrastructures [1]. Has incurred a new interdiscipline subject—econophysics [2]. The application of methodologies like stochastic dynamics, self-similarity, scale theory etc. Under this circumstance, complex network with abundant utilization of statistic physics can be judged as a branch of econophysics in relevant financial and industrial researches. Et al establishes networks of companies and branches in Poland through bipartite graph theory [3]. Inoue, et al investigate a PLOS ONE | DOI:10.1371/journal.pone.0156270 May 24, 2016
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