Improving diffusion in agriculture: an agent-based model to find the predictors for efficient early adopters

Abstract

Proven that the adoption rate of a new product is influenced by the network characteristics of the early adopters, the aim of this paper is to find the network features of the early adopters associated with high adoption rates of a specific new practice: the use of biodegradable mulching films containing soluble bio-based substances derived from municipal solid wastes. We simulated the diffusion process by means of an agent-based model calibrated on real-world data. Closeness and clusterization emerged as the most important network characteristics for early adopters to be successful. The results achieved represent the basis for the breaking down of a tailored diffusion strategy to overcome the psychological and socio-economic barriers of this kind of innovation within an environmental and sustainability-oriented transition policy in a rural context.