Original scientific paper

https://doi.org/10.17559/TV-20240828001945

Evolutionary Game Analysis of New Farmers in e-Commerce Chains

Lihong Sun ; School of Business Administration, Jiangxi University of Finance and Economics, Nanchang 330032, PR China; School of Business, Wuyi University, Wuyishan 354300, PR China *
Hui Shu ; School of Business Administration, Jiangxi University of Finance and Economics, Nanchang 330032, PR China

* Corresponding author.

Abstract

This study presents a rural e-commerce ecosystem model that underscores the synergistic efforts of multiple stakeholders in cultivating new farmers, a key driver in China's agricultural and rural modernization. We integrate a neural network into the evolutionary game framework and employ particle swarm optimization (PSO) to train it, simulating the learning and behavior of new farmers. The study applies this model to analyze the repeated Prisoner's Dilemma, revealing the PSO-trained neural network's efficacy in modeling the learning and strategy adjustment of bounded rational new farmers. Key findings include the significant influence of initial cooperative thresholds, investment costs, and collaborative surplus profits on strategic decisions for co-cultivating new farmers. The research contributes to rural revitalization strategies by highlighting the importance of cooperative mechanisms in fostering sustainable rural e-commerce development. The integration of PSO with neural networks to analyze evolutionary games represents a novel approach, offering a strategic roadmap for enhancing rural economic growth through new farmer cultivation.

Keywords

cooperative dynamics; e-commerce industry chain; evolutionary game algorithm; new farmers; rural economic development

Hrčak ID:

328564

URI

https://hrcak.srce.hr/328564

Publication date:

27.2.2025.

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