This base model uses an agent-based approach to represent heterogeneous farmers’ trading partners selection among multiple recipients (other farmers, village collectives, and firms). Each period, a potential transfer-out farmer decides whether to transfer based on a net-return versus transaction-cost trade-off; if transferring, the farmer selects the counterparty with the highest expected profit. Meanwhile, social learning—operationalized as logistic accumulation of neighborhood experience—continuously updates uncertainty, which in turn shapes transaction costs and subsequent decisions.

This is model that explores how a few farmers in a Chinese village, where all farmers are smallholders originally, reach optimal farming scale by transferring in farmland from other farmers in the context of urbanization and aging.

This model simulates how collective self-organisation among individuals that manage irrigation resource collectively.

This is an agent-based model of the implementation of the self-enforcing agreement in cooperative teams.

This is an agent-based model that simulates the structural evolution in food supply chain.

This is model that simulates how multiple kinds of peer effects shape the diffusion of innovations through different types of social relationships.

This model simulates how the strategy one manages time affect the well-being that he/she can obtain.