India has set ambitious climate action targets but is lagging on achieving them. In most sectors, from energy and transport to waste, the supply side has progressed rapidly. Infrastructure, markets, and policy increasingly offer viable and affordable low-carbon options. Witness, for instance, the surge in adoption of electric mobility. Overall, however, adoption of low-carbon choices by households remains low: whether it’s segregating waste at source, composting wet waste on site, switching to energy-efficient appliances, or installing rooftop solar panels. Technology and policy dominate the climate conversation. Continued progress in these areas is vital. But it’s not enough. With 72% of emissions globally coming from household-level choices, shifting these is essential to meaningful climate action. The missing piece is a focus on the demand side: consumers’ choices and the multifarious factors shaping them. Diagnosing and addressing consumer choice through behavioural science is key to climate action in India. Behavioural diagnosticsBased on extensive field research, my colleagues and I propose a simple but robust framework for behavioural diagnostics that examines the factors influencing households choices. Factors can either enable or block a target low-carbon behaviour. Factors can exist on the supply side (policies, technology, infrastructure, subsidies, penalties, etc.) or the demand side (citizens’ norms, values, beliefs, attitudes, sense of agency and community, and other relevant demographic and cultural factors).We illustrate this approach to behavioural diagnostics with examples across sectors. These examples draw on extensive field research we’ve performed across waste, transport, and energy in Panjim, Goa, Kolhapur, Maharashtra, Kuppam, Andhra Pradesh, Jaipur and Udaipur, Rajasthan, and Almora, Uttarakhand:Factors influencing the adoption of low-carbon choices by households: Examples from researchSupply-side enablersFactors related to infrastructure, government policies, marketplace, and technology that enable low-carbon choices by households.Examples: Reliable vendors for rooftop solar, energy-efficient appliances, or electric vehicles, trusted manufacturers, long warranty periods, and reliable servicing, low upfront costs, government subsidies, and/or short cost-recovery periods, reliable and well-connected public transit systems, walkable footpaths, reliable waste collection systems and efficient effective downstream handling of collected waste. Supply side barriersFactors related to infrastructure, government policies, marketplace, and technology that obstruct low-carbon choices by households.Examples: Unclear or constantly shifting policies, policies misaligned with on-ground realities and preferences (e.g. lack of adequate subsidy for hybrid rooftop solar systems, i.e. battery-backed systems), missing, overly technical, or ineffective awareness campaigns, gaps between transit system planning and commuters’ journey origins and destinations, paucity of certified green builders, unpredictable or infrequent waste collection, remixing of segregated waste on collection vehicles, or absence of low-carbon waste disposal mechanisms at the municipal level. (Watching waste get mixed on collection vehicles, or burned at municipal landfills, doesn’t exactly motivate households to spend time and energy segregating their waste.)Demand-side enablersFactors related to citizens’ norms, values, attitudes, knowledge and knowledge gaps, and other psychological, social, and cultural variables that enable low-carbon choices by households.Examples: Pro-environmental attitudes, concern with rising power bills, high post-purchase satisfaction and positive word-of-mouth for many low-carbon technologies, lived experiences of climate change, sense of community, sense of agency, connectedness with nature, neuroticism, conscientiousness. Unsurprisingly, individuals who feel connected to nature, feel a sense of personal responsibility for the commons, and are by personality prone to diligence as well as worrying – are likelier to adopt low-carbon choices.Demand-side barriersFactors related to citizens’ norms, values, attitudes, knowledge and knowledge gaps, and other psychological, social, and cultural variables that obstruct low-carbon choices by households.Examples: Widespread and culturally ingrained reluctance by households to handle their own waste, the belief that managing waste, generating power, or addressing climate change is not households’ responsibility, climate cynicism or ‘doomerism’, focus on short-term costs and benefits, fears about electric vehicles’ range, or rooftop solar safety, which are often ill-founded or outdated, low trust in climate technology, low trust in government. For instance, policies around solar subsidies are in frequent flux, with rumours as well as official announcements of impending phase-outs. This, combined with worries about certain solar brands going out of business, and being unable to honour warranties and service contracts, impedes rooftop solar adoption.Sectors vary in the degree to which household choices are shaped primarily by supply-side versus demand-side factors. For instance, an upper-middle class household in a house with a suitable roof can easily install rooftop solar panels or water heaters, and save money doing so. But, for a household to switch to public or non-motorised transport, infrastructural factors become key: well-planned transit networks, good inter-modal connectivity, and safe crossings and footpaths/bicycle lanes. Whether the question is ‘How do we get Indian households to segregate their waste?’ or ‘How do we incentivise green roofs?’ – for every target low-carbon behaviour, a diagnostics mapping is a vital first step. Tools of behavioural research, from semi-structured interviews and quantitative surveys to focus group discussions, elicit information from households, community leaders (e.g. secretaries of Residents’ Welfare Associations and municipal commissioners), and key decision-makers (e.g. heads of home builders’ or solar vendors associations) to identify challenges and opportunities within the fourfold framework outlined above.From diagnostics to solutionsDiagnostics mapping informs solutioning. We launch interventions on a pilot basis and scale up the interventions that work. This involves working with both households and the supply side: manufacturers, vendors, government officials, and municipal staff.For instance, for waste segregation at source, our work across cities finds that households lack clarity on which item goes where. This demand-side barrier we have successfully addressed via illustrated informational posters, presentations, and interactive games to reframe waste segregation as easy, attractive, and normal. The product lifecycle from manufacturing to ultimate disposal is often opaque to households. Citizens therefore underestimate, or just don’t think about, the downstream effect of their waste-related behaviours. This leads to low compliance with waste segregation mandates. We have successfully addressed this by illustrating, for instance, the ultimate destiny of a banana peel or a PET bottle depending on whether households do or don’t segregate their waste. Realising that household-level choices determine whether kitchen waste becomes compost or biogas, and plastic waste becomes clothing – or whether everything gets burned or dumped all together, poisoning the city’s water, air, and soil – has proved effective in incentivising segregation at source.On the supply side, we’ve worked with waste-collection vehicle drivers to understand the challenges they face in collecting segregated waste and maintaining collection in their vehicles. During the monsoons, for instance, collected dry waste develops mould, nullifying its resale value, we’ve worked with flatblocks to identify dry, elevated places where dry waste could be appropriately stored for weekly collection. We’ve worked with collection route supervisors and landfill supervisors to identify further barriers and ensure compliance. To keep higher-value dry waste out of burn-only landfills, we’ve linked housekeeping staff with dry-waste aggregators, thus incentivising housekeeping staff to become an additional link in the waste segregation process.For rooftop solar adoption, our fieldwork across cities repeatedly identifies a key demand-side enabler: after acquiring solar, many households experience high satisfaction and spontaneously sing the praises of solar in their social networks. Having a solar user in one’s neighbourhood, social, or professional network is a key predictor of adoption. To capitalise on this social contagion effect, we organise community sharing sessions where current and potential solar owners can freely exchange experiences and information. Our research further finds that, for potential users, knowledge is a key gap: they want to know exactly how much capacity they can install, how much rooftop space that would occupy, and the exact costs and payback periods. To address these gaps, we organise Q&A sessions with solar vendors and other technical experts who have up-to-date financial, subsidy, and technical information, we’re also working with partners to disseminate awareness of technical tools including solar potential maps.On the supply side, we find that solar vendors are often a consumer’s first and only point of contact with the solar infrastructure side. Extensive mystery shopping interviews with vendors – where we pose as potential consumers – suggest that, across states, vendors tend to use overly technical language, fail to mention specifics about subsidies (e.g. that only domestically produced options, which tend to be significantly more expensive, are eligible), or to adequately explain all available panel types and system types before making a recommendation. To address this, we’ve conducted vendor workshops where we exchange perspectives on barriers to adoption, share sales scripts based on our insights into households’ priorities and values, and co-develop tools that households need to guide and simplify their decision-making process.The bridge to policyThere’s often a gap between policies and on-ground realities. For instance, the PM Surya Ghar solar subsidy scheme was initially designed for on-grid solar systems, i.e. battery-less systems. But India is now facing a scenario where a huge percentage of the solar power we produce is never utilised. The existing power grid cannot handle excesses, and there’s nowhere to store this power. Complicating this problem is the fact that solar production peaks at midday, when many people are at work and overall power usage is low, conversely, demand peaks in the early mornings and evenings, when people are at home and using energy-intensive appliances.As policymakers recognise this gap – between solar subsidy structure and the kinds of solar India needs, and between peak solar generation and peak power demand – it is slowly being addressed. Many states now offer additional subsidies for hybrid, battery-backed rooftop solar. But these additional subsidies are small. Hybrid systems cost so very much more than on-grid systems that, to be effective, subsidy amounts must also be commensurately higher. India is also now rolling out demand flexibility measures and time-of-day tariffs. By financially incentivising households to shift their power usage to periods when solar output is high and overall power demand is low, we can utilise more of the solar power we’re already generating. We can thus lower peak demand – total power consumed in high-demand hours – and thus avoid building more power capacity, whether that’s coal plants or solar farms. But shifting ingrained habits of power usage is not easy. It will require rigorous behaviourally informed analysis and interventions to change households how and when households use electricity.There’s a wealth of rich insights from behavioural science that we must harness to more effectively drive the adoption of the climate transition at the level of households, communities, and decision-makers. Ideally, a rigorous analysis of on-ground behavioural realities would precede policy development rather than occurring reactively. India needs to embed behavioural science in climate policy design. We need to build a behavioural bridge to policy.If someone wants to get fit, they’ll need the appropriate infrastructure: perhaps an alarm clock, running shoes, and a gym membership. Equipment is necessary but not sufficient. Unless the person identifies and addresses their mental blocks, fears, values, attitudes, and beliefs around fitness – meaningful change will not happen. The person may find themselves repeatedly setting goals and failing to achieve them, making inconsistent progress, or solving one problem only to create another. What’s true for one person trying to get fit is true for India trying to achieve its climate goals. Infrastructure, policy, and the marketplace have made substantial progress. They must continue to do so – but in a way that’s shaped from the ground up by the social, psychological, and cultural realities shaping household choice. Across sectors, behavioural science is key to addressing the lag in Indian households’ adoption of low-carbon choices.Amita Basu leads the Behavioural Insights Lab at Transitions Research. Transitions Research works primarily with India’s mid-sized cities to co-create just transitions. The Behavioural Insights Lab harnesses insights from behavioural science to drive the adoption of low-carbon behaviour and develop behaviourally informed scale-up and policy recommendations. This article is informed by research conducted over the last few years on rooftop solar in Panjim, Kuppam, Jaipur, and Udaipur, on waste segregation in Kolhapur, Kuppam, and Almora, and on transport in Panjim. All our work has been conducted under Memorandums of Understanding with urban local bodies. Our overall sample size is 500+ households across sectors and cities. Research methods have involved mystery shopping, semi-structured interviews, surveys, and focus group discussions as well as roundtables, interviews with municipal officials and staff, and sector experts. Where possible, we quantitatively measure the effectiveness of pilot interventions.