Modelling social networks in innovation diffusion processes: the case of electricity access in rural areas

At least one billion people are expected to gain access to electricity in developing countries by 2040. In rural areas, off-grid electrification is expected to contribute to achieve this goal. The appropriate design of energy solution requires reliable forecasts of long-term electricity demand. Innovation diffusion models can help modelling the spread of electricity appliances in remote communities. However, as reliable demand models should capture the complex socio-economic dynamics of local developing contexts, we attempt to introduce an extra complexity in innovation diffusion models, i.e. the modelling of social networks. We rely on an ideal case of innovation diffusion in a rural community and we design some experiments to describe the effect of introducing social networks in diffusion processes. We model network-based diffusion scenarios through discrete agent-based modelling approaches, and we compare the results to continuous diffusion models simulated through a system-dynamics approach. The results suggest how the structure of the network may impact on timing needed to complete diffusion processes - from few months to more than 10 years - and on users' rates of adoption. Such understanding may be useful for local electricity utilities, which manage off-grid systems, when they make their investment plans for guaranteeing a positive return of investment.