Beyond Leaders and Laggards: A Typology of Renewable Energy Adoption Trajectories with Evidence from Off-Grid Communities

TL;DR

This paper develops a new analytical framework using a novel metric called ATI to classify renewable energy adoption trajectories in off-grid communities, revealing diverse paths and disparities crucial for targeted policy strategies.

Contribution

It introduces the Adoption over Time Index (ATI) and a typology of eight adoption trajectories, including two newly identified paths, enhancing understanding of renewable energy diffusion dynamics.

Findings

Identification of eight distinct adoption paths, including two new trajectories.

Substantial presence of retreating and declining paths in off-grid communities.

Significant regional disparities and widespread lagging clusters in adoption levels.

Abstract

Understanding the dynamics of renewable energy adoption is essential for designing strategies that accelerate its spread - an urgent priority for advancing climate goals and improving well-being, especially in off-grid regions facing energy poverty. This study introduces a time-series-based analytical framework that quantifies and classifies adoption behaviors of geographic entities within a region. A novel metric, the Adoption over Time Index (ATI), captures cumulative adoption intensity and identifies shifts in adoption trends, improving the ability to distinguish between fundamental adoption paths. By combining ATI with three key features found to be indicative of adoption dynamics, we define a typology of eight distinct paths, including two newly identified trajectories - the decelerating path and the declining moderate path. Applying this framework to a case study of an off-grid Bedouin population in southern Israel reveals that these retreating paths exist in substantial proportions. Identifying such trends is critical for addressing stagnation and preventing backsliding in the diffusion process. The leaping path, by contrast, was nearly absent. We also identify behavioral diversity within both front-runner and trailing groups. Differentiating among these groups can help tailor acceleration strategies. The analysis further reveals significant disparities in adoption levels across the region, with lagging clusters being widespread and overall adoption falling short of the region's potential.