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 agentbased 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 socioeconomic barriers of this kind of innovation within an environmental and sustainability-oriented transition policy in a rural context. Here, we stress that, at the core of the diffusion process, there are operation and functioning of the social networks (i.e., the set and pattern of support, friendship, and communication relations) connecting people (Valente 1995). In fact, in its straightforward definition, the diffusion of innovation can be intended as "a special type of communication, in that the messages are concerned with new ideas" (Rogers 2003: 5). Communication implies the mobilization of social ties among people to create and share information and reach a reciprocal understanding (Rogers 2003). This process is fundamental in overcoming the innovation resistance that is the agents' normal response against uncertainty and the costly readjustment activity imposed by the Agricultural and Food Economics

Visual Uniqueness: An Unsupervised Contrast Learning Approach

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Analysis of the Effectiveness of Promotion Strategies of Social Platforms for the Elderly with Different Levels of Digital Literacy

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