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

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 Erdos-Renyi (ER), Barabasi-Albert (BA), Bianconi-Barabasi (BB) network models.