Classifying and aligning financial incentives for disaster-resilient housing: a framework from Sri Lanka - Frontiers

Front. Built Environ. , 19 August 2026

Sec. Sustainable Design and Construction

Volume 12 - 2026 | https://doi.org/10.3389/fbuil.2026.1853930

Building the Future: Building Resilience, Climate Adaptation, and Performance Optimization in Extreme Scenarios

Empirically derived classification of financial incentives and enabling mechanisms for disaster-resilient housing.

1. Sri Lanka Institute of Information Technology, Colombo, Sri Lanka

2. Loughborough University, Loughborough, United Kingdom

3. University of Huddersfield, Huddersfield, United Kingdom

Recurring disaster-related damage to housing highlights the need for mechanisms that can encourage investment in resilience before and after hazard events. Although grants, loans, insurance incentives, tax measures and pricing instruments have been examined individually, limited empirical research explains how these mechanisms can be classified and aligned with specific resilience interventions, or the conditions under which they can be combined, within housing governance and financial systems in developing-country contexts. This study examines how financial incentives can support disaster-resilient housing in Sri Lanka.

A qualitative multiple-case study was conducted in the disaster-prone districts of Ratnapura, Kegalle and Kalutara. Data were collected through 52 semi-structured interviews with policymakers, disaster management and local government officials, financial and built-environment stakeholders, housing owners and community-level participants. The data were analysed using a hybrid deductive–inductive thematic approach and compared across stakeholder groups and case-study districts. The preliminary framework was subsequently reviewed through two district-level validation workshops and an institutional consultation.

The analysis generated 67 methods and approaches organised across thirteen housing resilience interventions. Six financial incentive types were identified: Funding Assistance, Pricing Signals, Tax Adjustments, Money Market Interventions, Facilitation and Disincentives, with Law Enforcement retained as a separate enabling mechanism. The findings show that instrument choice is conditional rather than uniform: effective design requires combinations of financial, regulatory, institutional and capacity-building measures selected according to hazard conditions, household financial capacity and implementation context. The findings also highlight the need to balance risk-reflective mechanisms with affordability and distributional equity.

The resulting Multi-Dimensional Financial Incentive Framework classifies incentive mechanisms and aligns them with specific housing resilience interventions, and specifies the conditions under which instruments may be combined. As a framework that is empirically grounded rather than implementation-tested, it offers a context-sensitive basis for policy design, financial-sector engagement and post-disaster Build Back Better investment, and a foundation for subsequent empirical testing.

The year 2023 only recorded a total count of 399 disaster-related events, causing 86,473 fatalities to human lives and victimizing over 90 million people worldwide. The economic losses from the disaster events exceeded USD 200 billion ( UNDRR, 2024 ; Université Catholique de Louvain, United States Agency for International Development (USAID) ( Centre for Research on the Epidemiology of Disasters, 2024 ). Natural hazards are a result of natural environmental consequences and will lead to a disaster situation ( UNDRR, 2020 ). A disaster is defined as a solemn disruption to societal functions resulting in extensive human, economic and environmental losses to the system, which is ideally beyond the capacity of the affected community to handle by themselves ( UN, 2022 ; Wannous and Velasquez, 2017 ). Therefore, disasters are not only implications of natural environmental consequences but rather a mix of such consequences and the vulnerability of the communities in the affected areas ( Rehak et al., 2019 ; Peng et al., 2013 ). Exponential population growth, urbanisation, and economic and social disparities have increased communities’ vulnerabilities, leading to significant losses from natural hazards ( Ashlin and Ladle, 2007 ).

A large proportion of the losses taking place due to natural hazards and their consequences is attributed to the physical damage in the housing sector ( Johnson, 2017 ; McDonald, 2007 ). According to UNISDR and ARISE (2017) , each year, approximately 13.9 million people worldwide lose their homes due to on-set disasters such as floods, earthquakes, and cyclones. From these losses, building collapses account for the most devastating effects after a natural hazard, especially during earthquakes ( Kenny, 2009 ). This pattern continues from the past till present, for instance, during the Great Hanshin Awaji Earthquake in 1995, more than 6,000 lives were lost, and 80 per cent of the mortality occurred in collapsed houses ( GAR, 2011 ). From the latest evidence, the Turkey earthquake series was the costliest disaster of the year 2023, with a large number of building collapses and causing economic damages exceeding USD 5 billion in total ( UNDRR, 2024 ). Furthermore, hazards like floods cause relatively low mortality; however, they devastate many houses. For example, in the Indian state of Orissa, 265 floods with similar low mortality rates destroyed more than half a million houses ( GAR, 2011 ). The devastating flooding in Libya in September 2023, which affected nearly 20% of the total population, more than 70% of the reconstruction cost is attributed to the critical infrastructure, with the housing sector being its largest component ( World Bank, 2024 ).

During natural hazards and their consequences, countries with substandard houses and their inhabitants are reported to suffer most severely ( Comerio, 2004 ; Comerio, 1997 ; Global Program for Resilient Housing, 2019 ). People who reside in insecure, hazardous, overcrowded, low-quality housing, especially those located in disaster-prone geographical areas, such as flood plains, or unsettled, unstable ground conditions, experience a high level of exposure ( Paidakaki, 2012 ). During the last four decades, the world population grew by 87 per cent, while the number of people in flood plains has increased by 114 per cent and in cyclone-prone coastlines by 192 per cent. Simultaneously, the average annual damages over two 10-year periods from 1976 to 1985 and from 2005 to 2014 have increased more than tenfold in numbers from $14 billion to over $140 billion ( Hallegatte et al., 2017 ).

Furthermore, with the rapid urbanisation, the population living in substandard housing is expected to increase. Households with low-income levels often reside in mobile or poorly constructed houses and experience severe impacts during hazards ( Paidakaki, 2012 ). Poor and marginalised households face more significant difficulties in absorbing and recovering from the impacts of natural hazards as their houses are comparatively more vulnerable to disasters ( UN-Habitat, 2019 ). According to Hallegatte et al. (2017) , the poorest 20% of the world’s population in terms of consumption are 1.8 times more likely to reside in housing susceptible to disaster risk. In investigating the use of financial incentives to enhance the investment on housing sector resilience, the fieldwork was based in Sri Lanka, which was among the top three countries in terms of weather-related loss events in 2017 and the second highest in the Climate Risk Index based on fatalities and economic losses due to extreme weather events.

Damage to housing represents one of the most visible, immediate and socially disruptive consequences of natural hazards. While the physical destruction of dwellings results in the direct loss of shelter, its impacts extend far beyond the built asset itself. Housing damage can generate cascading consequences for household livelihoods, health, education, social stability, asset security, displacement patterns and long-term recovery trajectories ( Comerio, 1997 ; Paidakaki, 2012 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ). These impacts are particularly severe in developing-country contexts, where rapid urbanisation, insecure land tenure, informal and non-engineered construction, weak enforcement of planning and building regulations, and household poverty increase exposure and vulnerability to hazards such as floods, landslides, cyclones and coastal events ( Comerio, 1997 ; Bosher et al., 2016 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ).

Accordingly, disaster-resilient housing cannot be understood solely as a technical or engineering concern. Although hazard-resistant construction, retrofitting, drainage provision, retaining structures, site selection, land-use control and early warning systems are central to reducing physical vulnerability, their adoption is shaped by wider institutional, financial, behavioural and socio-economic conditions. Built environment resilience literature emphasises that resilience is a multi-dimensional capacity involving technical, organisational, social and economic dimensions rather than a single structural attribute ( Bruneau et al., 2003 ; Bosher et al., 2016 ; Cutter et al., 2013 ). Within the housing sector, technical resilience relates to the quality of design, construction materials, structural integrity, retrofitting measures and site-specific risk reduction. Organisational resilience depends on the effectiveness of local authorities, planning systems, building control, disaster management institutions and inter-agency coordination. Social resilience is shaped by community networks, local knowledge, preparedness, trust, participation and collective action. Economic resilience concerns the ability of households, businesses, financial institutions and public agencies to absorb losses, access finance, maintain livelihoods and support recovery after disaster events ( Bruneau et al., 2003 ; Cutter et al., 2013 ; Bosher et al., 2016 ).

This multi-dimensional understanding is especially important in developing country housing systems, where vulnerability is rarely produced by technical deficiencies alone. Instead, housing risk is often embedded within broader conditions of affordability constraint, informal construction practice, limited access to professional and technical advice, weak regulatory enforcement, fragmented institutional responsibility and inadequate access to appropriate housing finance ( Malalgoda et al., 2014 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ). Consequently, improving disaster resilience in the housing sector requires more than the availability of safer building technologies. It also requires governance arrangements, financial mechanisms, regulatory incentives and enabling systems that can motivate and support households, developers, local authorities, construction actors and financial institutions to invest in resilience before disasters occur.

Sri Lanka provides a relevant and contextually significant case for examining disaster-resilient housing because of its recurrent exposure to multiple hazards, including floods, landslides, cyclones, droughts, coastal erosion and tsunami risk. As an island state located in the Indian Ocean, the country’s settlement patterns, infrastructure systems and housing stock are repeatedly affected by hydro-meteorological and geophysical hazards. The housing sector has experienced extensive damage during major disaster events, most notably the 2004 Indian Ocean tsunami and the 2016 and 2017 floods and landslides. The 2004 tsunami caused widespread destruction of housing and built environment assets, while the 2017 floods and landslides affected multiple districts and generated substantial housing recovery and relocation needs ( Karunasena and Rameezdeen, 2010 ; GFDRR, 2017 ; IOM, 2017 ).

The Sri Lankan housing sector also reflects several structural vulnerabilities commonly observed in developing-country housing systems. These include substandard housing conditions, informal and non-engineered construction practices, settlement expansion into hazard-prone areas, insecure or constrained land availability, inadequate infrastructure provision, limited household access to finance, and uneven enforcement of planning and building regulations. Previous studies on the Sri Lankan built environment have further identified weak regulatory frameworks, unauthorised development, fragmented institutional arrangements, inadequate local-level capacity, limited funding, shortage of qualified technical personnel and governance-related constraints as barriers to achieving disaster resilience in the built environment ( Malalgoda et al., 2014 ; ADPC, 2009 ).

Although Sri Lanka has developed disaster management institutions and hazard mapping initiatives, a persistent challenge lies in translating risk information into risk-informed housing decisions at household, community and local authority levels. In practice, settlement and construction decisions are often shaped by affordability constraints, land scarcity, livelihood needs, access to services and limited awareness of long-term disaster risk. Consequently, households may continue to occupy or construct dwellings in hazard-prone locations, while local authorities may face capacity and resource constraints in enforcing land-use planning, building standards and relocation measures. This creates a gap between the availability of disaster risk knowledge and the practical implementation of resilient housing measures.

This context makes Sri Lanka an appropriate case for studying financial incentives for disaster-resilient housing. The central issue is not only whether resilient housing technologies, risk information or planning instruments are available, but whether households, builders, developers, local authorities and financial institutions have sufficient motivation, capacity and resources to adopt and implement them. A financial incentive framework for Sri Lanka must therefore respond to both the technical requirements of resilient housing and the socio-economic, institutional and financial conditions that shape housing decisions. Examining Sri Lanka as a developing-country case allows the study to investigate how financial incentives can be adapted and operationalized in contexts where housing vulnerability, affordability constraints, informal construction and local governance limitations intersect.

A persistent challenge in disaster risk reduction is the chronic underinvestment in resilience before disaster events occur. Although the economic and social benefits of resilience are widely recognised, investments in risk reduction often involve high upfront costs, while the benefits are realised over longer time horizons and may be uncertain, indirect or distributed across multiple actors ( CISL, 2016 ; Watson et al., 2015 ; Hallegatte et al., 2017 ; Levy, 2018 ). This creates a financing and incentive problem: the actor expected to bear the immediate cost of resilience may not be the only or primary beneficiary of the avoided future loss. In the housing sector, this problem is particularly acute because households often face competing livelihood priorities, limited savings, constrained access to formal credit and uncertainty regarding future hazard exposure and potential losses ( Fothergill and Peek, 2004 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ).

The economic rationale for investing in resilient housing is well established. Mitigation, retrofitting, safer site selection and resilient construction can reduce future physical damage, lower reconstruction costs and limit social and economic disruption after disasters ( Bosher et al., 2016 ; Hallegatte et al., 2017 ; Global Program for Resilient Housing, 2019 ). However, the existence of positive long-term returns does not automatically translate into household, market or institutional investment decisions. Homeowners may delay or avoid retrofitting because they cannot afford the initial cost, underestimate disaster risk, lack technical guidance, prioritise immediate consumption needs, or expect post-disaster assistance from government, donors or social networks. Similarly, developers and contractors may avoid resilient features where these increase construction costs without producing immediate market premiums or regulatory advantages. Financial institutions may also be reluctant to support resilient housing where disaster risk is not adequately incorporated into lending, valuation, mortgage, insurance or collateral assessment systems ( Kunreuther et al., 2016 ; Levy, 2018 ; NIBS, 2015 ).

This situation reflects a wider implementation gap between the recognition of disaster-resilient housing as a policy priority and the practical conditions required to make resilience investment financially attractive and institutionally feasible. In many developing-country contexts, this gap is intensified by informal construction, limited insurance penetration, weak enforcement of building regulations, inadequate household savings and fragmented institutional responsibilities ( Malalgoda et al., 2014 ; UN-Habitat, 2019 ). Consequently, resilience cannot be advanced through technical recommendations alone. It requires financial and governance mechanisms that reduce upfront costs, improve access to affordable finance, make disaster risk visible in housing and land-use decisions, reward risk-reducing behaviour and discourage unsafe or non-compliant construction practices. Financial incentives are therefore important not merely as funding tools, but as mechanisms for reshaping the economic conditions under which households, developers, local authorities and financial institutions make housing investment decisions.

Financial incentives can be understood as policy, market or governance instruments that alter the economic conditions under which actors make decisions. In disaster risk reduction, they are used to encourage households, developers, contractors, financial institutions and public authorities to adopt risk-reducing behaviours that may exceed minimum compliance requirements or may not otherwise be financially attractive ( ADB, 2016 ; Watson et al., 2015 ). Within the housing sector, such incentives can reduce the upfront cost of resilient construction, support retrofitting, encourage relocation from high-risk locations, promote compliance with building codes, improve access to credit, reward risk-reducing behaviour and discourage practices that increase disaster risk ( CISL, 2016 ; Hallegatte et al., 2017 ; Levy, 2018 ).

The relevance of financial incentives arises from the fact that housing decisions are shaped not only by technical knowledge, but also by affordability, perceived risk, access to finance, market signals and regulatory enforcement. Even where resilient construction technologies or retrofitting methods are available, households and developers may not adopt them if they increase immediate costs without generating visible short-term benefits. Financial incentives therefore function as mechanisms for correcting or reducing this investment gap by redistributing upfront costs, internalising disaster risk, improving affordability and aligning private decisions with public resilience objectives ( Kunreuther et al., 2016 ; NIBS, 2015 ; Watson et al., 2015 ).

The literature identifies several categories of financial incentive mechanisms relevant to disaster-resilient housing. Funding assistance includes grants, subsidies, mitigation funds, relocation assistance, social protection transfers and post-disaster reconstruction support, which reduce the immediate financial burden of resilience measures ( Hallegatte et al., 2017 ; Global Program for Resilient Housing, 2019 ). Credit-based incentives include concessional loans, microfinance, home improvement loans, mortgage-linked resilience products and savings instruments that improve access to capital for households, developers and contractors ( GAR, 2011 ; NIBS, 2015 ; Palmamarisa and Garcia Lozano, 2017 ). Insurance-related incentives include premium reductions, risk-based pricing, microinsurance and insurance-linked resilience requirements, which can make risk-reducing behaviour financially attractive while supporting disaster risk transfer ( Kunreuther et al., 2016 ; Levy, 2018 ; Colby and Zipp, 2021 ). Tax adjustments, such as deductions, exemptions and credits, can reduce the fiscal burden of resilient construction, retrofitting or the use of hazard-resistant materials ( Adams, 2015 ; GAR, 2011 ). Pricing signals, including permit fees, development charges, stormwater fees, land-use charges and risk-reflective pricing, can make disaster risk visible in housing, land and infrastructure decisions ( Levy, 2018 ). Disincentives, such as penalties for unsafe construction, illegal development, non-compliance with building codes or damage to protected areas, can discourage risk-generating practices by making them financially unattractive ( ADB, 2016 ; Watson et al., 2015 ).

In addition to direct monetary instruments, the literature also recognises the importance of enabling mechanisms that support the uptake of financial incentives. Facilitation measures such as technical advice, awareness programmes, financial literacy support, training for builders, community workshops and coordination platforms may not constitute direct financial transfers, but they require resource allocation and are essential for enabling households and practitioners to understand, access and apply incentive schemes effectively ( Archer et al., 2020 ; Cutter et al., 2013 ; UN-Habitat, 2019 ). Similarly, regulatory enablers such as building codes, land-use planning controls, construction permits, completion certificates and risk-sensitive design requirements are not financial incentives in themselves, but they create the institutional conditions within which financial incentives can function effectively ( Bosher et al., 2016 ; Moullier and Sakoda, 2018 ; Malalgoda et al., 2014 ).

A limitation in the existing literature is that many formally documented examples of financial incentives are derived from developed-country contexts, particularly in relation to insurance pricing, mortgage-linked incentives, tax concessions and municipal pricing instruments. These examples are useful because they demonstrate the underlying mechanisms through which financial incentives can shape housing decisions, such as cost reduction, risk internalisation, access to credit, fiscal relief, behavioural deterrence and regulatory compliance ( NIBS, 2015 ; Adams, 2015 ; John, 2013 ; Levy, 2018 ). However, they should not be treated as directly transferable policy models for Sri Lanka or other developing-country contexts. Developed-country incentive systems often assume formal property markets, higher insurance penetration, functioning mortgage systems, reliable hazard data, stronger local government capacity and more consistent regulatory enforcement. These assumptions may not hold in contexts where informal construction, affordability constraints, limited access to formal finance, low insurance uptake and fragmented institutional responsibilities shape housing decisions ( Malalgoda et al., 2014 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ).

For this reason, developed-country examples are treated in this study as mechanism precedents rather than policy templates. Their value lies in identifying broad incentive logics that can inform the design of locally appropriate mechanisms. The empirical task is to examine how these incentive logics can be adapted, combined and operationalised within the Sri Lankan housing context. This requires moving beyond isolated instruments towards a context-sensitive framework that connects financial incentives with governance capacity, regulatory enforcement, household affordability, construction practices, local knowledge and disaster risk management systems.

While developed country examples provide useful evidence of possible incentive mechanisms, the conditions under which these mechanisms operate differ significantly from those in developing-country housing systems. It is therefore necessary to examine Global South evidence to understand how financial incentives can be adapted where affordability constraints, informal construction, local governance capacity and community-level implementation strongly influence housing decisions.

Evidence from the Global South suggests that financial incentives for disaster-resilient housing cannot be designed as stand-alone financial products. In developing-country contexts, incentive mechanisms are more likely to be effective when they are embedded within broader systems of local governance, capacity development, land-use planning, community participation, social protection and post-disaster recovery planning ( ADB, 2016 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ). This is because housing vulnerability in such contexts is shaped not only by the affordability of resilient construction, but also by informal building practices, insecure land tenure, uneven regulatory enforcement, limited technical guidance and restricted access to formal finance. Accordingly, the effectiveness of financial incentives depends on the institutional and social systems through which they are delivered.

Studies and policy experiences from Asian urban contexts provide useful insights for Sri Lanka. Incentive-based approaches to disaster risk reduction have been discussed in relation to land-use management, local government action, community engagement, urban risk governance and targeted public support in countries such as Viet Nam, Nepal and the Philippines ( ADB, 2016 ). Importantly, the incentives documented across these three cities were largely not designed with disaster risk reduction as their primary purpose. They operated instead through existing municipal, credit, land and planning systems, contributing to risk reduction indirectly or requiring only modification to do so directly ( ADB, 2016 ). This indicates that instrument combination in developing-country settings has typically emerged through the adaptation of established administrative and financial channels rather than through purpose-built resilience products. ADB (2016) further emphasises that the effectiveness of such incentives depends on an enabling environment, regulatory authority, local government capacity and risk information a conclusion consistent with the classification of Facilitation and Law Enforcement as conditions of incentive effectiveness in the present study.

These examples suggest that, unlike developed-market contexts where insurance, mortgage and tax systems often form the dominant incentive pathways, developing-country contexts frequently require stronger reliance on local authority capacity, community-based implementation, targeted grants, technical facilitation, risk-informed land-use control and public-sector coordination. Such evidence is particularly relevant to Sri Lanka, where housing decisions are shaped by affordability constraints, settlement pressures, local livelihood needs and varying local government capacity.

Microfinance and incremental housing finance literature also provides important lessons for incentive-based housing resilience in developing countries. Low-income households often construct or improve housing incrementally, making small investments over time rather than undertaking complete formal construction or major retrofitting at once. In this context, microfinance, savings groups, home improvement loans and community-based finance may support households to introduce progressive resilience improvements, such as drainage, raised plinths, retaining structures, stronger materials or safer extensions ( GAR, 2011 ; Palmamarisa and Garcia Lozano, 2017 ). However, credit-based incentives require careful design. Loans alone may be inappropriate for households that are already debt-constrained, have unstable incomes or lack collateral. Therefore, credit mechanisms may need to be combined with grants, subsidies, technical advice, social protection measures and community-based targeting to avoid increasing the financial vulnerability of at-risk households ( Hallegatte et al., 2017 ; UN-Habitat, 2019 ).

Post-disaster reconstruction literature further demonstrates the importance of linking financial assistance with Build Back Better principles. Following disasters, substantial funding often becomes available through government programmes, donor assistance, humanitarian support and household compensation schemes. If these funding flows are linked to safer site selection, resilient construction standards, technical guidance, livelihood recovery and local authority supervision, they can reduce future housing vulnerability and avoid reproducing pre-disaster risk conditions ( GFDRR, 2017 ; UNDRR, 2015 ; UNDRR, 2020 ). However, where post-disaster assistance is delivered primarily as compensation or replacement funding without resilience conditions, it may recreate unsafe housing patterns and reinforce dependency on reactive recovery finance. This indicates that financial incentive systems should not be designed only after disasters occur; they should be pre-arranged and integrated into disaster risk financing, housing policy, social protection, local planning and community preparedness systems.

The Global South literature therefore points to a different emphasis from much of the developed-country incentive literature. While developed-country examples often focus on insurance premium reductions, tax benefits, mortgage incentives and municipal pricing tools, developing-country contexts require stronger attention to affordability, informal construction, incremental housing practices, local governance capacity, social protection, community knowledge, targeted public grants, technical facilitation and enforcement capacity ( ADB, 2016 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ). This distinction is central to the present study. It supports the argument that financial incentives for disaster-resilient housing should not be transferred mechanically from developed contexts, but should be adapted to the institutional, financial and socio-economic realities of developing-country housing systems. In the Sri Lankan context, this requires examining how incentive mechanisms can be operationalised through local authorities, community actors, financial institutions, construction practitioners and national disaster governance systems.

The literature identifies a broad but fragmented range of financial and enabling mechanisms that may encourage investment in disaster-resilient housing. Direct cost-sharing mechanisms include grants, subsidies, social protection transfers, relocation assistance and post-disaster reconstruction funding, which reduce the immediate financial burden associated with safer construction, retrofitting and risk reduction ( CISL, 2016 ; Hallegatte et al., 2017 ; Global Program for Resilient Housing, 2019 ). Credit- and market-based mechanisms include concessional loans, microfinance, home improvement finance, mortgage-linked products, savings instruments and insurance-related incentives, which aim to improve access to capital, transfer disaster risk or reward risk-reducing behaviour ( GAR, 2011 ; NIBS, 2015 ; Kunreuther et al., 2016 ; Levy, 2018 ; Colby and Zipp, 2021 ). Fiscal and price-based mechanisms, including tax deductions, exemptions, permit charges, development fees and risk-reflective pricing, seek to influence housing and land-use decisions by reducing the cost of resilience or increasing the financial consequences of risk-generating development ( Adams, 2015 ; Levy, 2018 ).

The literature also recognises the role of disincentives and regulatory mechanisms in shaping resilient behaviour. Penalties for unsafe construction, illegal development and non-compliance with building standards can make risk-creating practices financially unattractive, while building codes, zoning controls, construction permits and land-use planning establish the institutional conditions within which incentive mechanisms operate ( ADB, 2016 ; Watson et al., 2015 ; Bosher et al., 2016 ; Moullier and Sakoda, 2018 ). These regulatory measures are not financial incentives in a strict sense, but they determine whether financial mechanisms can be targeted, monitored and enforced effectively.

In addition, developing-country literature highlights the importance of facilitation and capacity development. Technical advice, community awareness, builder training, financial literacy, local authority support and stakeholder coordination do not involve direct monetary transfers to households, but they require financial resources and can reduce informational, technical and institutional barriers to incentive uptake ( Archer et al., 2020 ; Cutter et al., 2013 ; UN-Habitat, 2019 ). This is particularly important in contexts characterised by informal construction, incremental housing development, limited access to professional advice and weak institutional capacity.

The existing mechanisms operate at several interconnected levels. Household- and property-level instruments include retrofitting grants, loans, insurance discounts and technical assistance. Community- and local-authority-level mechanisms include mitigation funding, community preparedness support, land-use controls, permit-related charges and local infrastructure investment. National and financial-system mechanisms include taxation, mortgage regulation, insurance policy, social protection and disaster risk financing. Private-sector mechanisms target developers, contractors, material suppliers and financial institutions through concessional finance, tax relief, pricing benefits and resilient technology support. The literature therefore suggests that housing resilience cannot be promoted through a single instrument; it requires coordination across household, community, market, local government and national policy systems.

However, the current knowledge base remains predominantly instrument focused. Grants, loans, insurance, tax benefits, pricing signals and penalties are commonly examined as separate policy tools, with limited explanation of how they should be combined within an integrated housing governance system. Moreover, many formally documented mechanisms originate from developed-country contexts characterised by formal property markets, higher insurance penetration, established mortgage systems, reliable hazard data and stronger regulatory enforcement ( NIBS, 2015 ; Adams, 2015 ; Levy, 2018 ). These examples provide useful evidence of possible incentive logics, but their direct transfer to Sri Lanka and comparable developing-country contexts is constrained by affordability pressures, informal construction, limited insurance uptake, uneven local authority capacity and fragmented institutional responsibilities ( Malalgoda et al., 2014 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ).

Accordingly, the literature establishes broad mechanisms through which financial incentives may influence resilient housing investment, but it does not provide a sufficiently integrated or context-sensitive classification for operational use in developing country housing systems. Literature was therefore used in this study as a source of sensitizing concepts rather than as a predetermined framework. The empirical investigation subsequently examined which mechanisms were considered feasible, how they should be classified, the resilience interventions to which they could be applied, and the institutional conditions required for their implementation in Sri Lanka.

The literature demonstrates that the challenge facing disaster-resilient housing is not the complete absence of financial incentive mechanisms. A diverse range of instruments has already been proposed or implemented internationally, including grants, subsidies, concessional loans, microfinance, insurance premium adjustments, tax concessions, risk-reflective pricing, penalties, social protection transfers and post-disaster reconstruction funding ( GAR, 2011 ; ADB, 2016 ; Kunreuther et al., 2016 ; Watson et al., 2015 ; Hallegatte et al., 2017 ; Levy, 2018 ). These mechanisms operate through different economic logics. Some reduce the upfront cost of resilient construction or retrofitting; some improve access to credit and risk-transfer mechanisms; others internalise disaster risk through prices, fees or insurance conditions; and some discourage unsafe development by increasing the financial consequences of non-compliance ( NIBS, 2015 ; Adams, 2015 ; Levy, 2018 ; Colby and Zipp, 2021 ).

Existing studies also indicate that financial incentives operate across several levels of the housing system. At the household and property level, instruments include retrofitting grants, home improvement loans, insurance discounts and technical assistance. At the community and local-authority level, mechanisms include local mitigation grants, drainage and infrastructure funding, permit-related pricing, community preparedness support and land-use controls. At the national and financial-system level, tax concessions, mortgage regulation, insurance policy, disaster risk financing and adaptive social protection can influence how public and private resources are directed towards resilience ( ADB, 2016 ; Hallegatte et al., 2017 ; Global Program for Resilient Housing, 2019 ). Private-sector actors, including developers, contractors, material suppliers and financial institutions, may also be influenced through concessional finance, tax adjustments, pricing advantages and support for resilient technologies ( NIBS, 2015 ; Watson et al., 2015 ).

This multi-level character indicates that financial incentives cannot be designed or implemented as isolated policy instruments. Their effectiveness depends on interactions among households, communities, local authorities, financial institutions, construction professionals, private-sector organisations and national government agencies. Financial instruments must also be supported by building regulations, land-use planning, technical guidance, institutional coordination and community-level capacity. Regulatory measures such as building codes, zoning controls, construction permits and risk-sensitive standards are not financial incentives in a strict sense, but they provide the institutional foundation required for incentives to be targeted, monitored and enforced effectively ( Bosher et al., 2016 ; Moullier and Sakoda, 2018 ; Malalgoda et al., 2014 ). Similarly, awareness programmes, technical advice, builder training, financial literacy and stakeholder coordination may not involve direct monetary transfers, but they require resource allocation and reduce the informational and institutional barriers that constrain incentive uptake ( Cutter et al., 2013 ; Archer et al., 2020 ; UN-Habitat, 2019 ).

Despite this breadth of knowledge, literature remains fragmented in three important respects. First, much of the formally documented evidence is derived from developed-country contexts characterised by relatively mature insurance systems, mortgage markets, formal property ownership, reliable hazard information and stronger regulatory enforcement ( NIBS, 2015 ; Adams, 2015 ; Kunreuther et al., 2016 ; Levy, 2018 ). These examples provide valuable evidence of how incentive mechanisms may influence housing decisions, but their direct transfer to developing-country contexts is limited. In Sri Lanka and comparable settings, affordability constraints, informal and incremental construction, limited insurance penetration, uneven access to formal finance, land scarcity and varying local authority capacity significantly influence housing decisions ( Malalgoda et al., 2014 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ).

Second, existing studies commonly examine grants, loans, insurance, tax concessions, pricing signals, penalties and post-disaster funding as separate instruments. Limited attention has been given to how these mechanisms should be combined within an integrated housing resilience governance system. In particular, the literature provides insufficient explanation of how financial mechanisms interact with land-use planning, building control, local authority capacity, community knowledge, construction practices, social protection and private-sector participation ( ADB, 2016 ; Watson et al., 2015 ; Bosher et al., 2016 ).

Third, limited empirical evidence explains how financial incentives can be operationalised across different levels and stakeholder groups within developing-country housing systems. Although the literature identifies numerous potential instruments, it provides less guidance on which mechanisms are appropriate for particular resilience needs, how they should be targeted, which actors should administer them, and what enabling conditions are required for their implementation. An operational approach must simultaneously consider household affordability, community-level mitigation, local government implementation, national policy alignment, construction-sector capacity, private-sector participation and financial-market involvement.

The resulting research gap is therefore not simply the need to identify additional financial instruments. Rather, there is a need for an empirically grounded and context-sensitive framework that explains how existing incentive mechanisms can be classified, combined, targeted and operationalised within a developing-country housing system. Such a framework must distinguish between direct financial incentives, indirect enabling mechanisms and regulatory conditions, while also linking these mechanisms to specific housing resilience interventions, implementation levels and stakeholder responsibilities.

The present study addresses this gap through a qualitative multiple-case investigation in three disaster-prone districts in Sri Lanka. International and developing-country literature is used as a sensitising foundation rather than as a predetermined classification. The empirical investigation subsequently examines how financial incentive mechanisms are understood, adapted and extended through expert, institutional and community-level evidence. The contribution of the study lies in developing an empirically grounded classification and alignment framework that integrates financial incentives with governance arrangements, regulatory enablers and practical housing resilience intervention domains. In doing so, the study advances the existing knowledge base from a fragmented collection of financial instruments towards an integrated governance–finance–housing resilience framework appropriate to Sri Lanka and potentially adaptable to comparable developing-country contexts.

This study adopted an interpretivist qualitative multiple-case study design to examine how financial incentives could be structured and operationalised to promote disaster-resilient housing in Sri Lanka. This design was appropriate because the study investigated context-dependent perceptions, institutional arrangements, financial constraints and implementation conditions that could not be adequately understood through quantitative indicators alone ( Saunders et al., 2019 ; Yin, 2014 ). The unit of analysis was the use of financial incentives to promote disaster resilience within the housing sector.

Ratnapura, Kegalle and Kalutara were purposively selected as geographically bounded cases because they had experienced substantial housing impacts from recent floods and landslides and represented contrasting hazard and implementation contexts. Ratnapura and Kegalle provided evidence concerning landslide exposure, slope instability and relocation, while Kalutara provided stronger evidence concerning flood-related housing damage, drainage and evacuation needs. The multiple-case design enabled both within-case examination and cross-case comparison of common and context-specific incentive requirements.

The research process comprised seven stages: review of the literature; collection of experts, institutional and community evidence; thematic coding; within-case analysis; comparison across cases and stakeholder groups; development of the preliminary framework; and review and refinement through validation workshops and an institutional consultation.

Participants were selected purposively according to their knowledge or direct experience of disaster risk management, housing governance, financial systems, construction practice, local administration, housing vulnerability or post-disaster recovery. Initial participants were identified from relevant national, district, professional and community stakeholder groups, with snowball referrals used where necessary to access additional information-rich participants.

A total of 52 semi-structured interviews were conducted. These comprised 15 expert and institutional interviews with policymakers, disaster management authorities, financial-sector representatives, housing and building authorities, local government officials and built-environment professionals, together with 37 case-study interviews involving housing owners and other community-level stakeholders across Ratnapura, Kegalle and Kalutara. The sample was designed to provide evidence from actors involved in designing, regulating, implementing and receiving financial incentives rather than to achieve statistical representation.

Expert and institutional participants contributed policy, regulatory, technical and financial-system perspectives, while case-study participants provided evidence concerning disaster experience, housing conditions, affordability, relocation, access to finance, local coping practices and the perceived feasibility of proposed incentives. Participants were anonymized using the codes EX for expert and institutional participants and D1, D2 and D3 for participants from Ratnapura, Kegalle and Kalutara, respectively.

Data were collected primarily through semi-structured interviews held through face-to-face/online or both lasted approximately 30–90 min, and were conducted in English or Sinhalese. Semi-structured interviews allowed consistent exploration of the research objectives while enabling participants to introduce context-specific experiences and recommendations ( Barriball and While, 1994 ; Alshenqeeti, 2014 ).

The interview guides were developed from the research objective and literature-informed financial incentive concepts. Separate but related guides were prepared for expert/institutional and case-study participants. Both addressed five broad areas: disaster-related housing vulnerability; barriers to investment in resilience; existing financial, institutional and regulatory arrangements; potential financial incentives and enabling mechanisms; and conditions required for implementation. Expert interviews placed greater emphasis on policy design, financial instruments, regulatory feasibility and institutional responsibilities, whereas case-study interviews focused on lived disaster experience, housing damage, affordability, access to finance, relocation, coping strategies and the acceptability of proposed incentives. Selected disaster risk reduction policies, housing reports, disaster impact assessments and recovery documents were reviewed to establish the policy and case-study context. These materials, together with contextual field notes generated during case visits, were used to support interpretation and triangulation but were not analyzed as an independent primary dataset.

Ethical approval was obtained from the University of Huddersfield. All participants received information about the purpose of the study, voluntary participation, confidentiality, data use and their right to withdraw. Written or recorded informed consent was obtained before each interview.

With participants’ permission, interviews were audio-recorded, transcribed and checked against the recordings for accuracy. Interviews conducted in Sinhalese were translated into English. Identification information was removed, and the anonymized transcripts, field notes and analytical records were stored securely.

Credibility was strengthened through the inclusion of multiple stakeholder groups, comparison across three cases, contextual documentary review and validation of the preliminary framework. Dependability and transparency were supported through systematic coding in NVivo, maintenance of an audit trail, iterative review of codes and themes, and an evidence matrix linking each method or approach to its empirical source. Direct participant quotations were retained in the Results to demonstrate the connection between interpretation and evidence.

The interview data were analysed in NVivo using a hybrid deductive–inductive thematic approach. The deductive component used concepts derived from the literature and research objective as sensitizing codes, including Funding Assistance, Pricing Signals, Tax Adjustments, Money Market Interventions, Facilitation, Disincentives, regulatory conditions and housing resilience. These concepts guided initial coding without predetermining the final classification. The inductive component captured additional issues arising from participants’ accounts, including affordability, relocation constraints, local authority capacity, informal construction, community knowledge, social capital, secondary risks, workforce capacity and post-disaster financial management.

Analysis proceeded through five connected stages. First, transcripts and field notes were repeatedly reviewed to develop familiarity with the data. Second, meaningful segments were assigned initial deductive or inductive codes. Third, related codes were consolidated into higher-order financial incentive categories and resilience interventions. Fourth, within-case findings were compared through a case-by-theme matrix covering Ratnapura, Kegalle and Kalutara. This matrix was then extended to compare expert/institutional and community-level perspectives, enabling the analysis to identify convergence, divergence and hazard-specific priorities. The purpose of the comparison was interpretive rather than numerical; recurrence across sources strengthened confidence in a finding but was not treated as a measure of statistical prevalence.

Fifth, the resulting methods and approaches were mapped simultaneously against their financial incentive or enabling mechanism and the resilience intervention they supported. Each method included in the final 67-item matrix was required to be traceable to at least one empirical data source.

Alongside this mapping, the analysis retained the conditions participants attached to individual methods; the household or institutional circumstances under which an incentive was considered appropriate, the responsible actors, and the regulatory or capacity requirements that needed to precede it. These conditional and relational codes informed the cross-case synthesis and provide the basis for the intervention-level decision logic presented in the Results. Literature-informed concepts that were not supported by the empirical evidence were treated as sensitising concepts rather than reported as study findings. This process generated six financial incentive types; Funding Assistance, Pricing Signals, Tax Adjustments, Money Market Interventions, Facilitation and Disincentives, with Law Enforcement retained as a separate enabling mechanism, and thirteen housing resilience interventions.

The preliminary Multi-Dimensional Financial Incentive Framework was subsequently constructed by integrating the incentive categories, resilience interventions, stakeholder perspectives, hazard-specific requirements and implementation conditions.

Following the thematic analysis and cross-case synthesis, the preliminary framework was reviewed through two district-level validation workshops and one institutional consultation. The district workshops were conducted at the Kegalle and Ratnapura Divisional Secretariats and involved 15 participants: eight in Kegalle and seven in Ratnapura. Participants included district administrative officials, disaster management officers, National Building Research Organisation representatives, officers responsible for land and human settlements, and local development officers working in disaster prone areas. A separate consultation was conducted at the National Building Research Organisation headquarters in Colombo with nine senior technical and managerial participants.

Participants reviewed the relevance and clarity of the incentive categories, resilience interventions and associated methods and considered their practical feasibility, institutional responsibilities and compatibility with existing governance arrangements. They were also invited to identify missing mechanisms, unclear classifications and additional regulatory, technical or coordination requirements.

Workshop and consultation feedback was compared with the original interview evidence and cross-case findings. It was used to refine category descriptions, clarify implementation responsibilities and strengthen the framework’s emphasis on local adaptation, inter-institutional coordination, technical Facilitation, monitoring and Law Enforcement. This process established the framework’s perceived relevance and contextual applicability among implementation stakeholders; it did not constitute a test of operational effectiveness, which requires subsequent piloting through an actual housing or disaster risk reduction programme.

This section addresses the principal objective of the paper: to explore the methods and approaches through which financial incentives can promote disaster resilience in the housing sector. The thematic and cross-case synthesis of expert interviews and the Ratnapura, Kegalle and Kalutara case studies generated 67 methods and approaches. These were organised through two complementary classifications.

The first classification concerns the mechanism through which resilience-related behaviour can be influenced. Six financial incentive types were identified: Funding Assistance, Pricing Signals, Tax Adjustments, Money Market Interventions, Facilitation and Disincentives. Law Enforcement emerged as a separate enabling category. Funding Assistance, Pricing Signals, Tax Adjustments and Money Market Interventions were classified as direct financial incentives because they alter the availability, cost or terms of financial resources. Facilitation and Disincentives were classified as indirect financial incentives: Facilitation requires financial resources to address technical, informational and institutional barriers, while Disincentives influence behaviour through adverse financial implications. Law Enforcement was retained separately because it establishes the regulatory conditions necessary for the incentives to operate but does not necessarily involve a monetary reward or implication.

The second classification concerns the area of resilience to which each method is directed. Thirteen resilience interventions were identified: Institutional Intervention, Land Use Planning, Physical/Structural Resilience, Community Engagement, Technological Advancement, Emergency Management and Response, Community Wellbeing, Capacity Development, Nature-Based Solutions, Private Sector Participation, Disaster Risk Transferring, Financial Management and Local Economic Resilience.

The two classifications explain both how an incentive operates and where it may be applied. The findings consequently indicate that financial incentives should not be implemented as isolated instruments. Their effectiveness depends on alignment with the relevant resilience requirement, hazard context, stakeholder group and level of governance. The complete mapping of the 67 methods and approaches is provided in Supplementary Table S1 .

Table 1 summarizes the principal function, representative applications and empirical interpretation of each incentive or enabling mechanism.

Funding Assistance emerged as the most widely applicable direct financial incentive, spanning household-level measures such as relocation, resilient construction and retrofitting, as well as collective interventions including drainage, retaining structures, evacuation facilities, early-warning systems, Nature-Based Solutions and local mitigation projects. Its prominence reflected a consistent mismatch between recognised resilience needs and the financial capacity of households and implementing institutions.

Affordability was the principal constraint. As one Kalutara participant explained, “Our financial difficulties are even worse than these; that is why we take all these troubles to stay in the same house even during hazardous conditions. But not fully constructed houses, instead, all of them are partly built, and we do not have sufficient funds further to complete them” (D3.4). Continued exposure was therefore not necessarily attributable to limited risk awareness, but to households’ inability to complete construction, retrofit existing dwellings or relocate. Relocation was further constrained by land availability; a Ratnapura official noted that “the land is scarce” (D1.2), resulting in assistance being concentrated primarily on households formally classified as high risk and leaving some medium-risk households without a viable resilience pathway.

The findings also demonstrate that Funding Assistance is required for risks extending beyond the individual dwelling. In one case, a visible crack on an upper slope threatened thirteen households, yet neither the community nor the local authority had sufficient resources to undertake mitigation, forcing residents to evacuate during periods of heavy rainfall. This illustrates the need for locally administered grants for collective interventions whose benefits and costs cannot be assigned to a single household.

At the same time, the evidence revealed the continuing fiscal burden of reactive assistance. One Ratnapura official reported that “last year we have spent around Rs. 480,000.00 for giving cooked meals” (D1.2), while another participant referred to compensation of “Rs. 10,000 as a means of covering the damages caused due to floods” (D1.6). Although such expenditure addressed immediate needs, it did not reduce recurrent exposure. The findings therefore support redirecting part of post-disaster expenditure towards proactive mitigation, resilient reconstruction and Build Back Better measures.

Overall, Funding Assistance is best understood as a differentiated cost-sharing mechanism rather than a uniform cash transfer. Its design should distinguish between household retrofitting, relocation, collective mitigation and institutional or infrastructure investment, while considering income, hazard exposure, intervention cost and expected public benefit.

Pricing Signals included risk-sensitive permit and land pricing, insurance premium reductions, favourable pricing for resilient materials and technologies, and benefits linked to Nature-Based Solutions. Their purpose was to incorporate disaster risk into present housing and investment decisions, particularly where comparatively inexpensive land in hazard-prone areas attracts financially constrained households.

However, risk-reflective pricing creates an equity concern: higher development costs may discourage unsafe construction while further restricting access to housing for low-income households. Pricing Signals should therefore consider household income and operate alongside Funding Assistance, relocation support and Social Protection Schemes.

Insurance premium reductions were identified as a potential positive Pricing Signal, but insurance had limited community acceptance. Participants observed that “currently insurance is perceived as an extra cost” (D1.1) and that “the general public does not see insurance as a solution but rather an additional cost” (D1.6). Thus, premium adjustments alone may be insufficient; their effectiveness also depends on affordability, awareness, trust and a clear link between verified resilience measures and financial benefits.

Tax Adjustments were mainly proposed by expert participants and targeted contractors, developers, technology providers and other private-sector actors through relief for resilient construction, technologies and Build Back Better reconstruction.

The findings suggest that Tax Adjustments may be more effective as supply-side incentives than as direct household benefits because these actors influence the cost, availability and quality of resilient construction. As one expert explained, “This will work mostly in the private sector, especially for the contractors who have a short-term interest in the housing buildings. If you give a tax incentive or a funding grant, they will be more motivated to build resilient housing” (EX3). Tax incentives can therefore help align short-term commercial interests with the longer-term safety of homeowners and communities.

However, such benefits should be conditional on demonstrated resilience performance. One expert noted that “the councils were giving grants to the housing owners on the condition that they adopt a high level of specifications” (EX6). The same principle applies to Tax Adjustments, which should be linked to approved standards, technologies or verified resilience outcomes rather than provided as general construction subsidies.

Money Market Interventions included concessional loans, preferential interest rates, finance for resilient technologies and equipment, contractor and developer lending, and emergency or contingency savings mechanisms. These instruments address the mismatch between the immediate cost of resilience and the longer-term benefit of avoided losses.

The findings also indicate that access to finance can be linked to compliance with resilience requirements. As one participant explained, “We usually provide them guidelines asking them to adhere to those, then only we re-consider those applicants and provide the loan scheme for them” (D1.2). Loan schemes can therefore function not only as sources of capital but also as mechanisms for encouraging risk-sensitive design and construction.

Effective implementation nevertheless requires financial-sector coordination. An expert noted that “If you are considering incentives such as money market instruments, reduced loan rates, they need to be coordinated and collaborated with the banking sector” (EX8). Such interventions should therefore be developed jointly by banks, regulators, housing authorities and disaster management institutions.

The findings also caution against treating credit as universally appropriate. Households with irregular or daily-wage incomes may have limited repayment capacity. A differentiated model is therefore required, combining grants for highly vulnerable households, blended grant–loan arrangements for those with partial repayment capacity, and preferential finance for contractors, developers and financially stable households. Emergency savings and contingency funds may further strengthen preparedness, although their feasibility depends on the regularity and adequacy of household income.

Facilitation was the most extensive indirect financial incentive category, encompassing technical advice, community awareness, financial literacy, workforce training, early-warning education, institutional coordination, indigenous knowledge and community leadership. Its prominence demonstrates that financial resources alone are insufficient: households must understand available interventions and funding schemes, builders require risk-sensitive construction knowledge, and officials need the capacity to assess and monitor implementation.

As one expert observed, “Through awareness workshops and programs, it is important to enhance the education on building resilience and what to do when a disaster strikes” (EX4). Facilitation therefore supports both preventive action and emergency preparedness.

The findings also highlighted the value of local knowledge. One participant explained that “After all heavy rain, mudslides develop when water rapidly accumulates in the ground and results in a surge of water-saturated rocks” (D1.6), reflecting community understanding of rainfall, soil saturation and landslide warning signs. Another proposed that “What we can do is planting necessary trees to this region, that could inevitably mitigate the risk up to a considerable level. Trees like mahogany, rubber are ideal” (D1.3), illustrating how local experience may inform potential Nature-Based Solutions.

Facilitation therefore extends beyond awareness raising. It reduces information and capacity gaps, strengthens access to financial incentives and creates a platform through which community knowledge can be integrated with technical assessment and formal resilience planning.

Disincentives comprised financial penalties for non-compliance with construction standards, environmental damage and illegal or unsafe development. Participants viewed these measures not only as restrictions but also as mechanisms for protecting collective safety. As one Ratnapura participant stated, “Penalties should be there so that if anyone clears forests, cuts down trees or engages in illegal constructions, the officers can soon activate to take the necessary actions against such things in those people’s region” (D1.4).

However, penalties alone may be ineffective or inequitable where compliance is unaffordable, or formal approval procedures are inaccessible. Disincentives therefore require clear standards, consistent enforcement, simplified regulatory procedures, technical guidance and financial support for households unable to meet resilience requirements independently.

Law Enforcement included local authority powers, land-use controls, building standards, permits, completion certificates, settlement restrictions and resilience conditions attached to financial support. The findings showed that financial incentives may fail to reduce exposure where the necessary legal provisions are absent.

An expert illustrated this through post-2017 resettlement: “There is a resettlement scheme for the high-risk category housing owners in the Sri Lankan context after the 2017 disasters. However, as there is no law to take back the high-risk lands after resettling in new locations still, the communities reside in the original locations after receiving the financial benefit for relocation” (EX6). This demonstrates that relocation funding alone cannot ensure risk reduction unless the conditions attached to assistance and the future use of unsafe land are legally defined.

Community participants similarly supported stronger controls, stating that “the government should implement new laws and rules … [and] obstruct or completely control new settlements in risk-bound areas” (D2.14). Law Enforcement therefore provides the basis for eligibility, compliance, monitoring and accountability. Although distinct from financial incentives, it is essential to their effective implementation.

The second classification organised the 67 methods and approaches according to thirteen resilience interventions. Although analytically distinct, several interventions were closely interrelated and are therefore synthesised below to demonstrate how financial incentives operate across the wider housing system.

Institutional Intervention concerned the authority, resources and coordination required to administer financial incentives, while Land Use Planning addressed settlement location, environmental protection, development approval and hazard exposure. The findings indicate that incentives require institutions capable of identifying risk, allocating support and monitoring compliance; as one expert observed, “the incentive policies will be initiated by the national government level, but there needs to be the right coordination for these to be successful” (EX9). Proposed approaches included appointing officials responsible for housing resilience, strengthening local authority powers, incorporating regional hazards into construction standards, linking permit charges and financial eligibility to local risk conditions, controlling settlement in high-risk areas, protecting natural buffers and requiring permits and completion certificates. Collectively, the findings demonstrate that financial support should not be provided independently of housing location, hazard exposure and regulatory compliance.

Physical/Structural Resilience included relocation, resilient new construction, retrofitting, raised floor levels, retaining structures, drainage, local mitigation projects and climate-sensitive infrastructure. The required interventions varied according to hazard context: flood-prone communities prioritised raised floors, drainage, evacuation facilities and warning communication, whereas landslide-prone communities emphasised retaining structures, slope mitigation, settlement control and relocation. The findings therefore do not support a uniform national incentive package; Funding Assistance and Money Market Interventions should be linked to locally appropriate technical measures, while Facilitation and Law Enforcement are required to support informed implementation and compliance.

These interventions encompassed community-led projects, local knowledge, social networks, leadership, Social Protection Schemes and the technical capacity of communities, public officials and construction-sector actors. The case studies showed that families, neighbours and community groups already contributed to warning, evacuation and recovery, suggesting that financial incentives should strengthen these capacities through local grants, participatory workshops, leadership development and community-based planning rather than positioning residents solely as recipients of assistance. Capacity Development was equally necessary among builders, engineers, architects, material suppliers and field officers, as financial assistance without adequate technical knowledge may support reconstruction without producing meaningful improvements in resilience.

Technological Advancement included weather monitoring, early-warning technologies, secondary-risk assessment, resilient equipment and locally available construction technologies, while Nature-Based Solutions comprised environmental measures supported through grants, subsidies and favourable finance. The findings indicate that resilient technologies must be affordable, locally available and understood by users and practitioners, requiring incentives for households as well as contractors, suppliers and technology providers. Nature-Based Solutions similarly require community knowledge to be integrated with technical and environmental assessment, and their implementation intersects with Land Use Planning, Facilitation, Funding Assistance and Disincentives, particularly where natural buffers require protection and long-term maintenance.

Emergency Management and Response included warning posts, evacuation resources, emergency training, early-warning workshops and accessible communication systems. Participants recognised that Physical/Structural Resilience cannot eliminate all risk; one resident reported that officials had “asked us not to stay in these places during heavy rains but to rescue ourselves by fleeing to safer zones” (D1.5). This demonstrates the continuing importance of warning and evacuation arrangements, although repeated evacuation should not substitute for permanent mitigation or relocation where these are technically and financially feasible. Financial support for emergency response should therefore complement rather than replace longer-term resilience investment.

These interventions addressed the roles of contractors, developers, financial institutions, insurance providers, household savings and local businesses. Private Sector Participation was supported through Tax Adjustments and Money Market Interventions aimed at encouraging resilient construction, technology adoption and investment; Disaster Risk Transferring focused on affordable insurance and resilience-linked policy requirements; Financial Management included emergency savings and guidance on using compensation for risk reduction; and Local Economic Resilience incorporated business continuity planning, contingency finance and livelihood protection. The findings demonstrate that resilient housing depends on income continuity, functioning markets, construction services and access to materials, requiring insurance, savings, Funding Assistance and Social Protection Schemes to operate as complementary components of a layered financial protection approach.

Several methods recurred across Ratnapura, Kegalle and Kalutara, including grants and loans for retrofitting, local mitigation funding, early-warning education, local knowledge integration and technical capacity development, indicating that affordability, access to finance, knowledge and institutional capability were common concerns. However, the priorities varied by hazard context: landslide-prone areas placed greater emphasis on relocation, retaining structures, slope mitigation and settlement control, whereas flood-prone areas prioritised raised floors, drainage, evacuation facilities and warning communication. Stakeholder perspectives also differed, with community and local-level participants focusing on immediately accessible measures such as grants, loans, relocation, drainage and technical advice, while expert participants emphasised Tax Adjustments, financial-sector coordination, Private Sector Participation, insurance conditions, Build Back Better and regulatory reform. These perspectives were complementary, demonstrating that an effective incentive approach must combine local affordability and practical feasibility with institutional, financial and market coordination.

Building on the empirical findings, the study developed a Multi-Dimensional Financial Incentive Framework that integrates the 67 identified methods and approaches across two interrelated dimensions: the thirteen resilience interventions and the six financial incentive types, with Law Enforcement retained as a separate enabling mechanism. Funding Assistance, Pricing Signals, Tax Adjustments and Money Market Interventions represent direct financial incentives, while Facilitation and Disincentives operate indirectly by reducing implementation barriers or imposing financial consequences on risk-generating behaviour. Law Enforcement provides the regulatory foundation required to establish eligibility, compliance, monitoring and accountability. The framework therefore moves beyond a catalogue of individual instruments by demonstrating how different incentive types can be aligned with specific areas of housing resilience, as illustrated in Figure 1 .

A multi-dimensional financial incentive framework for housing resilience.

The framework should not be interpreted as a fixed package requiring the simultaneous application of all incentives. Rather, it provides a flexible structure for selecting and combining methods according to the local hazard profile, required resilience intervention, household financial capacity, target stakeholder and institutional context. In this way, the framework connects household, community, market and governmental actions within a coordinated approach to disaster-resilient housing. The resulting classification is empirically derived rather than exhaustive. It reflects the incentive methods and enabling conditions prioritised by participants across the three case-study districts and the expert and institutional interviews, and it is therefore bounded by the Sri Lankan governance, hazard and socio-economic context in which the data were generated. The framework is presented as an extensible classification, open to refinement and addition as further contexts, hazard types and stakeholder groups are examined, rather than as a complete inventory of all possible financial incentives.

Figure 2 maps the identified methods and approaches across Institutional Intervention, Land Use Planning, Physical/Structural Resilience, Community Engagement, Technological Advancement, Emergency Management and Response, Community Well-being, Capacity Development, Nature-Based Solutions, Private Sector Participation, Disaster Risk Transferring, Financial Management and Local Economic Resilience. The framework demonstrates that most resilience interventions require a combination of incentive types rather than a single financial instrument.

Alignment of the 67 identified methods and approaches with housing resilience interventions by incentive type.

For example, as demonstrated in Figure 3 household retrofitting can be structured as a sequence rather than a simultaneous bundle. The intervention begins with identification of the resilience requirement, followed by assessment of household financial capacity, which determines instrument choice: Funding Assistance (grants) for households with limited repayment capacity, blended grant-loan arrangements for those with partial capacity, and Money Market Interventions for households with stable income. Facilitation operates throughout as an enabling condition, providing technical guidance and workforce capacity, while Law Enforcement acts as a compliance condition, with finance released against verified adherence to resilient construction standards. Consistent with participants’ emphasis on incremental provision, incentives can be linked to defined resilience milestones rather than disbursed at a single point. This illustrates how the framework functions as a decision structure: the incentive types are ordered, conditional on household capacity, and gated by compliance, rather than merely co-present. Similarly, community-level mitigation may depend on public funding, local institutional capacity, community participation and regulatory support. The framework should therefore be interpreted as a flexible decision structure rather than a fixed package requiring the simultaneous application of all incentives. The appropriate combination should be selected according to the local hazard profile, resilience requirement, household financial capacity, intervention scale, target stakeholder and institutional context. Although the framework is empirically grounded in the expert and cross-case findings, it represents a strategic structure rather than an implementation-tested model and consequently requires contextual adaptation, implementation planning and further practical evaluation.

Decision pathway for selecting and sequencing financial incentives for household retrofitting.

Instrument choice is triggered by an assessment of household repayment capacity, directing provision towards Funding Assistance, a blended grant-loan arrangement, or Money Market Interventions. Facilitation operates as a parallel enabling condition across all three finance routes, and Law Enforcement gates the release of finance against verified code-compliant design. The pathway illustrates how the framework functions as a decision structure rather than a co-occurrence matrix.

The central finding of this study is that financial incentives promote disaster-resilient housing not through isolated instruments, but through combinations of financial, institutional, regulatory and capacity-building mechanisms directed towards specific resilience needs. Existing literature demonstrates the potential of grants, concessional loans, insurance discounts, tax benefits, development-fee adjustments and penalties to influence resilience investment ( ADB, 2016 ; NIBS, 2015 ; Levy, 2018 ). However, these mechanisms are commonly examined separately, with limited explanation of how they interact across different components of the housing system. The present study confirms the relevance of these established instruments but extends the literature by integrating them within two interconnected classifications: six financial incentive types, with Law Enforcement as an enabling mechanism, and thirteen resilience interventions. This dual classification shifts the analytical focus from identifying available instruments to understanding how particular incentives can be aligned with defined resilience outcomes, stakeholder groups and implementation levels. The resulting framework therefore conceptualizes financial incentives as components of a wider housing resilience governance system rather than as stand-alone financial products.

The thirteen resilience interventions reinforce the established understanding that disaster resilience is simultaneously technical, organisational, social and economic ( Bruneau et al., 2003 ; Bosher, 2014 ). The prominence of Physical/Structural Resilience; through relocation, retrofitting, raised floor levels, retaining structures and drainage corresponds with literature emphasizing safer construction, building-code compliance and the upgrading of vulnerable housing stock ( GAR, 2011 ; Gautam et al., 2016 ; Moullier and Sakoda, 2018 ). Nevertheless, the findings qualify as a predominantly building-centered interpretation by demonstrating that the resilience of a dwelling depends equally on land-use decisions, infrastructure, institutional capacity, emergency systems, community networks, livelihoods and access to financial services. This supports Nicol and Knoepfel’s (2014) argument that housing functions within interconnected physical and institutional systems, while extending it by specifying the financial mechanisms through which these interdependencies may be addressed. The inclusion of Nature-Based Solutions and Local Economic Resilience further broadens the intervention space beyond conventional construction and retrofitting by recognising that environmental buffers, household income continuity and local business recovery influence the long-term functionality of housing.

The variation observed among Ratnapura, Kegalle and Kalutara also supports the literature’s emphasis on context-sensitive resilience planning. International guidance argues that building standards, land-use measures and risk-reduction strategies should respond to local hazards, geophysical conditions, construction cultures and resource capacities rather than being applied through uniform national prescriptions ( UN ESCAP, 2012 ; Moullier and Sakoda, 2018 ). The present study provides empirical support for this position; flood-prone communities prioritised raised floors, drainage, evacuation facilities and warning communication, while landslide-prone communities placed greater emphasis on retaining structures, slope mitigation, relocation and settlement control. The findings consequently challenge “one-size-fits-all” incentive schemes and indicate that the same financial mechanism may need to support different technical interventions depending on the hazard context.

The prominence of Funding Assistance and Money Market Interventions confirms the established view that high upfront costs and delayed resilience benefits are major causes of underinvestment ( CISL, 2016 ; Hallegatte et al., 2017 ; Levy, 2018 ). Previous studies identify grants, subsidies, social protection transfers, concessional loans and mortgage-linked products as mechanisms for overcoming this financing gap ( GAR, 2011 ; NIBS, 2015 ; Global Program for Resilient Housing, 2019 ). The present findings support these mechanisms but refine their application in two respects. First, Funding Assistance was required not only for household construction and retrofitting but also for collective interventions such as drainage, slope mitigation, warning systems and evacuation infrastructure, whose benefits cannot be confined to an individual property. Second, the findings support differentiated cost-sharing rather than uniform financial assistance. Grants are more appropriate for households with limited repayment capacity and for interventions with substantial public benefits, whereas loans and blended grant–loan arrangements may be better suited to households and market actors capable of contributing financially. This distinction is especially important in contexts characterised by irregular employment, limited household savings and incremental housing construction.

The findings similarly qualify for the transferability of Pricing Signals and Tax Adjustments documented in developed-country literature. Risk-sensitive insurance premiums, development charges and property prices can internalise disaster risk and reward resilient behaviour ( Kunreuther et al., 2016 ; Levy, 2018 ), while tax deductions and exemptions can offset the additional cost of retrofitting and hazard-resistant construction ( Adams, 2015 ; GAR, 2011 ). The empirical evidence nevertheless indicates that these instruments are unlikely to operate identically in Sri Lanka. Low insurance acceptance limits the immediate influence of premium reductions, while risk-reflective land or permit pricing may disadvantage households whose location choices are constrained by poverty and land scarcity. Pricing Signals therefore require Funding Assistance, relocation options and Social Protection Schemes to prevent risk internalisation from becoming an additional burden on already vulnerable households. Tax Adjustments may also have greater potential as supply-side incentives for contractors, developers and technology providers than as household incentives, given the prevalence of informal and incremental housing construction. The study thus confirms the underlying economic logic of pricing and taxation mechanisms while locating their practical relevance within the structure of the local housing market.

Facilitation emerged as a prominent category across the expert and case-study evidence. Existing literature already recognises that technical assistance, awareness, financial literacy, training and stakeholder participation enable the uptake of resilience measures ( Archer et al., 2020 ; Cutter et al., 2013 ; UN-Habitat, 2019 ). The specific contribution of the present study is not this general proposition but the reclassification of Facilitation from a supplementary communication activity to an indirect financial incentive positioned within the incentive taxonomy itself, which clarifies why direct financial resources may fail to convert into resilient outcomes in its absence. A grant or loan has limited value where households cannot identify an appropriate intervention, local builders lack risk-sensitive construction knowledge, or officials cannot assess and monitor implementation. The importance placed on local knowledge, community leadership, technical training and institutional coordination therefore reflects conditions in which the effective use of finance depends on strengthening the capabilities of both recipients and implementing actors. This is particularly relevant to developing country housing systems, where informal construction and uneven professional access weaken the assumption that financial provision alone will produce technically sound investment.

The findings on Disincentives and Law Enforcement similarly reinforce, but also qualify, the regulatory literature. Penalties can make illegal construction, environmental degradation and building-code non-compliance financially unattractive, consistent with the use of sanctions and regulatory incentives identified by ADB (2016) and Watson et al. (2015) . However, the study indicates that penalties may be ineffective or inequitable where standards are unclear, enforcement capacity is weak or compliant construction is unaffordable. Disincentives therefore need to be operated alongside technical guidance, simplified approval procedures and financial support. Law Enforcement was consequently distinguished from the financial incentive categories and positioned as their regulatory foundation. This distinction is analytically important because laws, land-use controls, permits and building standards do not themselves constitute monetary incentives; rather, they define the conditions attached to financial benefits and establish the authority required for implementation. The resettlement evidence illustrates this relationship particularly clearly: financial assistance may fail to reduce exposure where legal provisions do not regulate the continued occupation or use of the original high-risk land. The study therefore extends the literature by showing that regulatory capacity affects not only compliance but also whether financial incentives ultimately achieve their intended risk-reduction outcome.

Many frequently cited examples of housing resilience incentives originate in developed-country settings characterised by formal property markets, established mortgage systems, higher insurance penetration, reliable hazard information and comparatively strong regulatory enforcement ( NIBS, 2015 ; Adams, 2015 ; Levy, 2018 ). The findings of this study indicate that these examples are better understood as mechanism precedents than as directly transferable policy templates. In Sri Lanka, the effectiveness of financial incentives is shaped by land scarcity, informal construction, irregular income, limited savings, low insurance acceptance and uneven local institutional capacity. This finding aligns with research showing that developing-country housing vulnerability arises from the interaction of financial deprivation, insecure or hazardous locations, weak enforcement and restricted access to technical expertise ( Malalgoda et al., 2014 ; Hallegatte et al., 2017 ; UN-Habitat, 2019 ). The study adds empirical detail by demonstrating how these conditions alter the suitability of individual instruments: loans may increase indebtedness among households with unstable incomes; risk-sensitive prices may restrict access to housing; relocation assistance may fail where livelihood and social considerations are ignored; and grants may finance reconstruction without improving resilience where technical support and monitoring are absent.

These findings place distributional equity at the center of incentive design. Literature has previously cautioned that housing-safety policies should not make safe housing unaffordable to low-income communities ( Fothergill and Peek, 2004 ). The present study reinforces this concern and demonstrates that risk-reflective incentives must be balanced by compensatory and enabling mechanisms. For example, higher charges for risky development may need to be accompanied by affordable safer land, relocation support or Social Protection Schemes, while resilience-linked lending should distinguish between households able to repay, those able to contribute partially and those requiring grant-based assistance. The framework therefore supports incremental and differentiated incentive packages rather than blanket eligibility rules. Such differentiation is not simply a matter of administrative targeting; it is necessary to prevent resilience policy from transferring disproportionate costs to households already exposed to socio-economic vulnerability.

The theoretical contribution of the study lies in connecting two bodies of knowledge that are often discussed separately: the literature on housing resilience interventions and the literature on financial incentives. Previous studies establish that financial incentives can reduce costs, improve access to capital, reward risk reduction and discourage unsafe behaviour ( ADB, 2016 ; Watson et al., 2015 ; Levy, 2018 ), but provide limited guidance on how these instruments should be combined and directed across the housing system. By mapping Funding Assistance, Pricing Signals, Tax Adjustments, Money Market Interventions, Facilitation and Disincentives supported by Law Enforcement, against thirteen resilience interventions, the framework provides an empirically grounded explanation of how financial mechanisms can support technical, institutional, social, environmental and economic resilience. It further clarifies the conceptual boundaries between direct financial incentives, indirect financial incentives and regulatory enabling mechanisms, thereby reducing the tendency to treat all resilience-supporting actions as equivalent forms of financial inducement.

From a practical perspective, the framework should be used as a decision structure rather than as a universal package. Its application begins with the identification of the hazard and resilience requirement, followed by an assessment of the target actor’s financial capacity, the appropriate incentive mechanism, the responsible institution and the regulatory or facilitative conditions needed for implementation. This approach is consistent with the Sendai Framework’s emphasis on investing in disaster risk reduction for resilience but provides greater operational specificity for the housing sector by identifying where investment can be directed and how stakeholder behaviour may be influenced. The framework also supports the strategic use of post-disaster finance by linking reconstruction funding with Build Back Better requirements rather than restoring pre-disaster vulnerability.

Nevertheless, the framework is empirically grounded rather than implementation tested. The qualitative evidence establishes the relevance, perceived feasibility and interrelationships of the proposed mechanisms, but it does not demonstrate their causal effectiveness, fiscal affordability or long-term distributional consequences. Practical application will therefore require pilot testing, cost–benefit assessment, legal and institutional review, clear eligibility criteria and monitoring indicators. These limitations do not diminish the value of the framework; rather, they define its current contribution as a context-sensitive foundation for policy design and further empirical evaluation.

This study examined how financial incentives can be structured to support disaster-resilient housing within the institutional, financial and socio-economic conditions of Sri Lanka. The findings demonstrate that the challenge is not simply a shortage of financial instruments, but the absence of an integrated mechanism for aligning finance with specific resilience needs, stakeholder capacities and governance arrangements. Grants, loans, pricing measures and tax benefits are unlikely to generate durable risk reduction when they operate independently of technical guidance, regulatory enforcement, institutional coordination and household affordability.

The study contributes a Multi-Dimensional Financial Incentive Framework derived from 67 methods and approaches across thirteen housing resilience interventions. The framework distinguishes Funding Assistance, Pricing Signals, Tax Adjustments and Money Market Interventions as direct financial incentives; Facilitation and Disincentives as indirect financial incentives; and Law Enforcement as a separate regulatory enabler. Its principal contribution lies in connecting these mechanisms to defined technical, institutional, social, environmental and economic resilience interventions. It therefore advances the literature from an instrument-centred understanding of incentives towards a coordinated governance–finance approach to housing resilience.

The findings further show that incentive design must be context-sensitive and socially differentiated. Flood- and landslide-prone communities require different technical and financial responses, while household income, land availability, repayment capacity, construction informality and institutional capability shape whether particular mechanisms are feasible or equitable. Risk-reflective pricing and lending conditions may encourage safer decisions, but they may also deepen exclusion where households lack access to safer land or affordable finance. Effective incentive packages must therefore combine risk reduction with affordability safeguards, targeted assistance and appropriate regulatory support. The same principle applies to post-disaster finance: reconstruction funding should not merely replace damaged housing but should be linked to resilient standards, technical oversight and Build Back Better objectives.

The framework remains an empirically grounded strategic structure rather than an implementation-tested model. Its practical value will depend on pilot application, institutional ownership, legal feasibility, fiscal capacity and measurable risk-reduction outcomes. Future research should test different incentive combinations through housing retrofitting, relocation, community mitigation and reconstruction programmes, with particular attention to uptake, cost-effectiveness, equity, compliance and long-term behavioural change. Nevertheless, the study establishes a clear basis for shifting housing resilience finance from fragmented and reactive expenditure towards coordinated, anticipatory and risk-informed investment.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The participants provided their written informed consent to participate in this study.

SN: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review and editing. DA: Supervision, Writing – review and editing. RH: Supervision, Writing – review and editing.

The author(s) declared that financial support was not received for this work and/or its publication.

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

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The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fbuil.2026.1853930/full#supplementary-material

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built environment , classification framework , disaster resilience , financial incentives , housing , Sri Lanka

Nissanka S, Amaratunga D and Haigh R (2026) Classifying and aligning financial incentives for disaster-resilient housing: a framework from Sri Lanka . Front. Built Environ. 12:1853930. doi: 10.3389/fbuil.2026.1853930

Ana Paula Melo , Federal University of Santa Catarina, Brazil

Luis M. Triveño , World Bank, United States

Amber Khan , University of Washington, United States

© 2026 Nissanka, Amaratunga and Haigh.

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* Correspondence: Shavindree Nissanka, nacshavindree@gmail.com

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