Modelling Trading Networks and the Role of Trust

TL;DR

This paper introduces a simple dynamical model of trading networks that incorporates trust and price dynamics, showing good agreement with real data and insights into wealth distribution.

Contribution

The paper presents a novel dynamical model of trading networks that includes trust and price evolution, validated by numerical simulations and comparison with real data.

Findings

Model reproduces real trading data well

Trust influences trading decisions and wealth distribution

Different trading strategies impact societal wealth distribution

Abstract

We present a simple dynamical model for describing trading interactions between agents in a social network by considering only two dynamical variables, namely money and goods or services, that are assumed conserved over the whole time span of the agents' trading transactions. A key feature of the model is that agent-to-agent transactions are governed by the price in units of money per goods, which is dynamically changing, and by a trust variable, which is related to the trading history of each agent. All agents are able to sell or buy, and the decision to do either has to do with the level of trust the buyer has in the seller, the price of the goods and the amount of money and goods at the disposal of the buyer. Here we show the results of extensive numerical calculations under various initial conditions in a random network of agents and compare the results with the available related data. In most cases the agreement between the model results and real data turns out to be fairly good, which allow us to draw some general conclusions as how different trading strategies could affect the distribution of wealth in different kinds of societies.