Abstract

In most supply chains (SCs), transaction relationships between suppliers and customers are commonly considered to be an extrapolation from a linear perspective. However, this traditional linear concept of an SC is egotistic and oversimplified and does not sufficiently reflect the complex and cyclical structure of supplier-customer relationships in current economic and industrial situations. The interactional relationships and topological characteristics between suppliers and customers should be analyzed using supply networks (SNs) rather than traditional linear SCs. Therefore, this paper reconceptualizes SCs as SNs in complex adaptive systems (CAS), and presents three main contributions. First, we propose an integrated framework of CAS network by synthesizing multi-level network analysis from the network-, community- and vertex-perspective. The CAS perspective enables us to understand the advances of SN properties. Second, in order to emphasize the CAS properties of SNs, we conducted a real-world SN based on the Japanese industry and describe an advanced investigation of SN theory. The CAS properties help in enriching the SN theory, which can benefit SN management, community economics and industrial resilience. Third, we propose a quantitative metric of entropy to measure the complexity and robustness of SNs. The results not only support a specific understanding of the structural outcomes relevant to SNs, but also deliver efficient and effective support to the management and design of SNs.

Highlights

  • Chain management (SCM) has been an important and extensively investigated topic since its appearance in the early 1980s

  • As SW networks can efficiently transfer the information flows throughout the whole network rather than the regular and random networks, we suggested that efficient supply networks (SNs) should present a relatively short average path length and a relatively high clustering coefficient

  • Fourth, when a node was removed from the network, did its links disappear, but links between other nodes may have disappeared in the real case

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Summary

Introduction

Chain management (SCM) has been an important and extensively investigated topic since its appearance in the early 1980s. SNs have become a new analytic paradigm in SCM, and have been identified as regional clusters [2,3,4,6] or industrial sectors [4,7,8], and are well known as complex adaptive systems (CAS) [5,9,10,11,12,13,14,15,16] This new theory of SN is extremely valuable and more meaningful than traditional SCs, and both structural and relational characteristics in the SNs enable firms to activate existing partners and select appropriate cooperation partners [6,8,17]. SNs have been increasingly recognized to find new business partners, discover new opportunities, increase operational efficiency, inform strategic direction, and identify and develop new products and services [20]

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