Abstract

Understanding the factors that influence energy transitions at a household level, is essential for designing and implementing successful strategies to promote the uptake of cleaner fuels and deliver associated socio-economic benefits in the rapidly growing cities of the Global South. In India over 30 percent of urban households are still reliant on traditional fuels for some portion of their energy needs. Such fast-growing cities often display intra-urban inequalities of considerable magnitude which can condition individual access to resources and impact the effectiveness of energy provision strategies for individual city wards and districts. Intelligent use of data can play an important role in addressing this spatial inequality. Energy transitions are often conditioned by a complex interaction of economic and social factors. Analysis of targeted locally collected data in combination with secondary data sources can provide a means of identifying appropriate strategies and incentives for specific wards and communities that policy makers and planners can enact. In this paper we will use the results of a survey of 420 households in 7 city wards in Bangalore, India and show how this micro-scale survey data can be leveraged using a novel conceptual framework. The high resolution offered by the micro-scale dataset was used to identify 5 different clusters of households as a result of energy use patterns and associated non-income characteristics. These typologies may be used to inform policy makers, entrepreneurs, and engineers on the influence of non-income barriers to energy transition for different types of low-income communities.