A Networked Evolutionary Trust Game for the Sharing Economy

Abstract

In the sharing economy, trust is of higher importance than in regular B2C interactions because there is no transfer of ownership and transactions sometimes take place in private space. Chica et al. (2017) developed an evolutionary trust game to unveil occurring dynamics and explain how trust could evolve in the sharing economy. This thesis adds the variable of network structure for the network of possible interactions to their model. Using agent-based modelling, the model is ran on networks with varying levels of community structure, systematically varying average degree, the community connectedness and game payoffs. We find negative correlations for degree and it is suggested that having more isolated communities has a positive effect on trust, but this is highly dependent on the reward for cooperating. Chica et al. (2017) showed strong interdependence between players of different strategies and found a strong influence of payoffs on the dynamics. The current research shows that a strong interaction with network structure should also be considered. The presented findings progress the field of evolutionary game theory, by learning from a specific application. Furthermore, findings also suggest that sharing economy platforms could enhance trust by emphasising or creating communities, depending on the risk and how clear benefits are to users.