Analytical bi-level multi-local-world complex network model on fresh agricultural products supply chain

Yunqing Liu, ,Jiayu Zhuang,Jiajia Liu,Shiwei Xu

doi:10.25165/j.ijabe.20221501.6353

Abstract

Lately, in some regions and seasons in China, urban consumers have paid high in buying fresh agricultural products while farmers get unreasonable income from producing them. To seek the reason for the phenomenon and explore ways to simulate it, this study constructed and implemented a complex network model named the Bi-Level Multi-Local-World (BI-MLW model) with characteristics of an interdependent coupling relationship between its participants. To verify the validity of the model, this study implemented an experimental simulation under Small Decentralized Operation Mode (SDOM) and Large Centralized Operation Mode (LCOM) scenarios using Cucurbita pepo and Cucumber in the Tianjin area of China as sample empirical products. Results indicate that nodes do not increase edges rapidly which reflects that even large firms in agricultural business cannot occupy markets fleetly. Furthermore, under the SDOM scenario the BI-MLW model exposes scale-free features with a small average degree value and low average clustering coefficient, while under the LCOM scenario, the model displays a rising average clustering coefficient and a lowered average path length. Both of which are consistent with the common view in literature and features of reality. Thus, the BI-MLW model specially designed for fresh agricultural products supply chain can improve the descriptive ability than conventional Erdös-Rényi (ER), Barabási-Albert (BA), Bianconi-Barabási (BB) network models. Keywords: fresh agricultural products, supplying process, supply chain, complex network, multi-local-world model DOI: 10.25165/j.ijabe.20221501.6353 Citation: Liu Y Q, Xu S W, Liu J J, Zhuang J Y. Analytical bi-level multi-local-world complex network model on fresh agricultural products supply chain. Int J Agric & Biol Eng, 2022; 15(1): 208–215.

Highlights

Many complex systems are directly or indirectly related to people, where everyone influences the functioning of the network but not anyone controls the global behavior of the whole system, this is even truer due to the enormous number of participants in the agricultural supplying process.With the rapid development of modern Internet and logistics, the supply “chain” has gradually evolved into a “network structure”
A complex network model between participants in the supply network under Small Decentralized Operation Mode (SDOM) and Large Centralized Operation Mode (LCOM) scenarios was discussed in this study
The results showed that: 1) Network topology and its trading capacity vary under different operation scenarios

Summary

Introduction

Many complex systems are directly or indirectly related to people, where everyone influences the functioning of the network but not anyone controls the global behavior of the whole system, this is even truer due to the enormous number of participants in the agricultural supplying process.With the rapid development of modern Internet and logistics, the supply “chain” has gradually evolved into a “network structure”. The behavior dependence and coupling between the participants become increasingly close, and the characteristics of cooperative symbiosis and mutually beneficial coexistence become more and more obvious Farmers cannot perceive their state in the whole supplying system, so they cannot adjust their production scale and growth path to fit into the market, they cannot find the most suitable traders to raise their bargaining & risk resistance ability effectively. It is impossible for middleman & wholesalers to explore the most profitable upstream & downstream dealers. Inspect the dynamics of the supplying system from an overall point of view, improve the upward trading efficiency, and stabilize the supply system are in need imperatively

Methods

Results

Discussion

Conclusion