Guided by the analytical framework described above, the study employed focus group discussions as the primary method to examine suppliers’ experiences of climate risk, financing, and equity in practice. A scenario-based preference-ranking exercise, administered in a survey format, was embedded within each focus group to support comparison and prompt discussion, rather than to generate standalone survey data. This design enabled the study to capture suppliers’ feasibility judgements and priorities within the context of real-world service delivery.

Suppliers were asked to rank options across four preference areas:

(1)Climate-resilientWASHproducts they would be most likely to provide under climate stress. Options were tailored by supplier type and included bottled water distribution (suppliers sell treated drinking water in containers to households), community rainwater harvesting (suppliers invest in a shared rooftop collection and storage systems in their operational area), pumped water supply (suppliers sell water via small-scale piped water systems owned and operated by them), household water filters (point-of-use treatment devices sold to households), resilient latrines built on or above the house (suppliers install elevated or flood-resistant sanitation structures in households for a fee), and HandyPod sanitation systems (suppliers install modular, portable, above-ground toilet units suitable for flood-prone areas for a fee).

(2)Financinginstruments considered acceptable and feasible to support delivery. These included government loans (suppliers access public-sector credit and repay the loan over defined period of time), government-guaranteed commercial loans (suppliers access and repay bank loans backed partially by government guarantee), commercial loans without guarantees (suppliers access and repay market-rate loans), credit enhancement mechanisms (suppliers access and repay finance via risk-sharing arrangements that reduce borrowing constraints), government subsidies (suppliers receive non-repayable financial support from the government), donor grants or technical assistance (suppliers receive non-repayable external funding or advisory support), green bonds (suppliers raise capital through environmentally themed debt instruments and repay investors upon the bond maturity), and social impact bonds (suppliers raise capital through performance-based debt instruments and repay investors upon verified outcomes).

(3)Whetherclimate-resilientWASHservicesforpoorhouseholdsshouldbeprovidedfreeofcharge, with response options of yes, no, or not sure.

(4)Responsibilityforfinancingfreeprovision, with suppliers ranking alternative cost-sharing arrangements, including supplier-only contribution, supplier - government co-contribution, supplier - community - government co-contribution, and donor or philanthropic financing.

At the start of each focus group, suppliers collectively identified the most prevalent hazards affecting their operations over the past decade: intense rainfall, drought, storms, flooding, and rising temperatures. Drought was consistently ranked as the most concerning hazard, followed by storms and intense rainfall. Suppliers were then asked to rank WASH adaptation products and financing options under conditions of continued exposure to these hazards. No fixed future time horizon was imposed; instead, the scenario reflected ongoing climate variability based on recent experience.

In the Cambodian rural context, suppliers would receive capital—repayable (loans, bond-financed lending) or non-repayable (grants, subsidies)—or technical support to invest in climate-resilient WASH. Obligations differ by instrument: repayment of principal and interest (loans), performance delivery (social impact bonds), or no repayment (grants/subsidies). This ranking exercise was intentionally framed at a general level to assess relative acceptability of instrument types rather than detailed contractual terms (e.g., collateral, repayment schedules, risk-sharing). More specific design features will be developed and tested in subsequent pilot financing models.

Each adaptation product and financing instrument was presented using illustrated cards (in Khmer) displaying a picture and short description. The cards were placed on a poster board and used to facilitate the ranking and discussion. Rankings were collected individually where every supplier was provided with a paper survey containing the ranking questions. Suppliers completed the ranking tasks independently to ensure that preferences reflected individual assessments rather than negotiated group positions.

Following completion of the individual ranking survey, suppliers were invited to discuss their rankings collectively within the focus group. This discussion allowed suppliers to explain their reasoning, constraints, and trade-offs, providing qualitative context to support interpretation of the ranking data. The qualitative discussion was analysed alongside the descriptive statistics of ranking data to strengthen understanding of feasibility perceptions and risk considerations.

All focus groups were conducted in Khmer and facilitated by the author, supported by two Cambodian research consultants who acted as interpreters and research assistants. The author designed the ranking survey, which was translated into Khmer by the consultants. Participants completed the paper-based survey individually in Khmer; responses were later translated into English and entered into Qualtrics for data management and descriptive analysis.

Sessions were audio-recorded with consent, transcribed in Khmer, and translated into English. Translation accuracy was verified through joint review to ensure conceptual consistency, particularly for technical and financing terminology.

Supplier participants were recruited through village leaders via invitation letters issued by the Country Director of the local NGO implementing the project. These leaders, who had collaborated with the researcher previously, identified suppliers with direct experience in rural WASH service delivery. To minimise potential influence, invitations emphasised voluntary participation, confidentiality, and the independence of the research from funding decisions. Village leaders did not attend the sessions. Facilitators reiterated that there were no right or wrong answers, and the individual ranking exercise prior to group discussion helped reduce conformity bias.

Completed paper surveys were subsequently entered into Qualtrics, where the ranking instrument had been programmed for data capture and analysis. There were no missing responses for the ranking questions; therefore, no imputation or adjustment procedures were required. Descriptive statistics were used to calculate means and standard deviations for each ranked option, with lower scores reflecting stronger preference. The unit of analysis was the individual supplier respondent. Given the small sample size and exploratory design, bootstrapping was used to assess the stability of descriptive statistics rather than to support statistical inference. The bootstrapped estimates were thus used as a robustness check on central tendencies, not as a basis for hypothesis testing or generalisation. As with all small-sample descriptive approaches, bootstrapping does not address selection bias or representativeness, and findings are interpreted as indicative rather than generalisable.

Qualitative data from focus group discussions were analysed thematically using a coding framework aligned with the analytical framing and performed for each RQ. Coding followed three primary domains: (i) preference rationales linked to the ranking exercise; (ii) perceived risks and constraints, including financial, operational, and institutional risks; and (iii) exposure to climate stressors such as flooding, drought, and water-quality variability. This approach enabled integration of ranking outputs with discussion-based explanations, allowing preferences to be interpreted in relation to the suppliers’ lived experiences, business models, and risk environments.

Three focus groups were conducted in June-July 2023 with small-scale water and sanitation suppliers in rural Cambodia, combining facilitated discussion with a preference-ranking exercise. Approximately 50 suppliers were invited; 23 declined due to time constraints, resulting in 27 participants (6 female). Of these, 18 were sanitation suppliers and 9 were water operators. Table 1 presents the provincial distribution of participants, and Figure 1 maps the seven provinces in which the suppliers operate.

Table 1. Supplier participants and locations.

Figure 1. Geographic distribution of supplier participants in Cambodia.

Among the nine water operators, experience levels varied, with around half in business for fewer than six years and a smaller group operating for more than a decade. Formal education levels were generally low, with most operators having primary or lower-secondary education. Nearly all operated in rural areas, and the majority provided piped water services, with a smaller number engaged in bottled water distribution or water filtration. Piped water tariffs are government-regulated and relatively low, limiting revenue flexibility. Monthly revenues varied widely, though several operators declined to disclose income.

Sanitation suppliers were similarly small-scale and predominantly family-run, with limited formal education and workforces typically comprising fewer than ten people. Experience in the sector ranged from early-stage businesses to long-established operators. Most served rural markets, with some extending services to peri-urban areas. Core activities included latrine construction, material sales, and related services, with latrine building as the primary income source. Sales volumes and monthly incomes varied substantially, reflecting heterogeneity in business scale. Suppliers reported multiple climate-related challenges, including hard ground conditions, flooding, and drought, which directly affect construction costs and demand.

Overall, the supplier sample is heterogeneous but predominantly rural and small-scale, characterised by limited formal education, constrained pricing power, and high exposure to climate-related risks. These characteristics provide essential context for interpreting suppliers’ preferences regarding adaptation measures, financing options, and approaches to pro-poor service provision.

The preference-ranking exercise, interpreted alongside focus group discussions, reveals clear and internally consistent patterns in how suppliers prioritise climate adaptation measures, with distinct preferences across water operators and sanitation suppliers.

As shown in Table 2, water operators ranked bottled water distribution systems as the most preferred adaptation option under climate stress, followed by household water filters. Community rainwater harvesting ranked lower, while pumping services were consistently ranked lowest. Focus group discussions indicate that these preferences reflect operators’ experience of increasing operational challenges linked to flooding, water contamination, and seasonal variability.

Water operators reported that heavy rains and flooding introduce polluted surface water from agricultural runoff, increasing turbidity and contamination and requiring additional chemical treatment, labour, and electricity. Muddy water was reported to damage filtration systems and increase pumping costs, while flooding also raised the incidence of pipe breakages. Coping strategies included sandbagging storage tanks, raising pumps and electrical devices, and closely monitoring electricity use—measures that increase operating costs and labour demands.

During dry periods, operators, who were reliant on tube wells, described problems with manganese and lime contamination, requiring either additional treatment or sourcing water from other operators. One operator explained:

“We helped transfer water from the stream to sell to them. One tank of 2,000 litres costs from USD 10 to 12.50… where possible, we asked our partnered NGO to drill a well or dig a pond.” (Water operator, Pursat)

Seasonal demand fluctuations further shaped preferences. Operators noted that during the rainy season, many households switch to rainwater for drinking, reducing demand for piped water. Cultural perceptions were reported to influence these choices:

“Some people felt that pipe water is less clean than rainwater, so they use pipe water for washing clothes and animals, and collect rainwater for drinking.” (Water operator, Prey Veng)

Within this context, bottled water and filtration technologies were perceived to be more reliable and marketable options during climate stress, while pumping services were viewed as offering limited additional value because most households already rely on their own tube wells until these are exhausted.

Sanitation suppliers ranked resilient latrines built on or above the house as the most preferred adaptation measure, followed by HandyPod systems, while options outside their core business were ranked lower (Table 2). Focus group discussions revealed that flooding damages latrines and increases demand for more resilient designs, while droughts reduce household purchasing power and delay sanitation investments. Suppliers reported that hard ground conditions during droughts and flooding during the wet season increase labour requirements and construction costs, reinforcing preferences for adaptation measures aligned with existing construction practices and supply chains.

Table 2. Supplier preferences for climate-resilient WASH adaptation measures under climate stress.

Notestothetable: Rankings are based on the preference-ranking exercise embedded within focus group discussions; Lower mean scores indicate higher preference; “—” indicates options not presented to that supplier group.

These findings align closely with the analytical framework for RQ1, which conceptualises adaptation preferences as risk-management responses shaped by climate exposure, cost structures, and market feasibility, rather than technological novelty. Consistent with prior research, these small-scale suppliers in low-income and climate-vulnerable settings favour incremental and familiar adaptations constrained by operating margins, institutional context, and user behaviour ([1]; [10]; [28]; [9]).

To tighten integration between the ranking results and qualitative findings, Table 3 summarises the core coding outputs used to interpret adaptation preferences. Codes were developed around climate exposure impacts, operating cost pressures, revenue volatility, household behaviour, and affordability constraints. These mechanisms explain why incremental, business-aligned adaptations were prioritised over more capital-intensive or unfamiliar options.

Table 3. Summary of core coding outputs for RQ1.

Taken together, the coded qualitative evidence clarifies the mechanisms underlying the ranking results. For water operators, the preference for bottled water and filtration reflects strategies to manage quality risk, reputational risk, and revenue volatility under climate stress ([3]; [12]; [20]; [15]). The consistently low ranking of pumping services aligns with evidence that rural households rely on self-supplied groundwater until wells fail, limiting willingness to pay for alternative supply while increasing operators’ exposure to electricity and infrastructure risks ([14]; [12]).

For sanitation suppliers, higher rankings for resilient latrine designs and HandyPod systems reflect income-sensitive demand and the need to minimise construction and payment risk under climate variability ([17]; [8]; [22]; [10]). These patterns reinforce adaptation scholarship emphasising feasibility, path dependency, and local capacity as central to climate responses, particularly in WASH systems where technical, financial, and institutional constraints shape what adaptations can realistically be delivered and sustained ([1]; [7]; [28]; [9]; [23]).

The combined ranking and focus group findings therefore suggest that climate-resilient WASH adaptation in rural Cambodia is most likely to be adopted when it builds on existing supplier practices, consumer trust, and market norms, rather than assuming uptake of unfamiliar technologies or service models ([10]; [15]). The results also echo political economy analyses cautioning against adaptation strategies detached from delivery realities, particularly where climate finance and resilience agendas are insufficiently aligned with local delivery capacity and equity considerations ([24]; [15]; [27]).

The ranking exercise and focus group discussions reveal a clear divergence in financing preferences between water operators and sanitation suppliers, reflecting differences in cost structure, risk exposure, and business models (Table 4 and Table 5).

Water operators consistently ranked donor grants and technical assistance as the most acceptable financing options across adaptation measures, while commercial loans without guarantees and bond-type instruments ranked lowest. Government loans and government-guaranteed commercial loans occupied intermediate positions.

Focus group discussions indicate that these preferences are shaped by rising operating costs, tariff constraints, and exposure to climate-related risks. Operators described how flooding and heavy rains increase treatment costs due to polluted surface water, while muddy water damages filters and increases electricity consumption for pumping. Flooding also increases pipe breakages, forcing costly repairs. During dry seasons, tube-well operators reported manganese and lime contamination, requiring additional treatment or water purchases from other suppliers, often at the expense of profits. As one operator explained:

“We helped transfer water from the stream to sell to them. One tank of 2,000 litres costs from USD 10 to 12.50… where possible, we asked our partnered NGO to drill a well or dig a pond.” (Water operator, Pursat)

Governance challenges further compounded these risks. Operators in Kampong Speu described cooperation with local authorities to conserve water, which were undermined by unregulated activities. In Takeo, industrial pollution imposed both treatment costs and regulatory fees:

“There’s trash in the lake and it caused a bad odour… we tried using alum, PAC and wood charcoal. The problem is the cost of treatment of the bad odour, and the fee paid to the authority which can be up to USD 5,000-6,250 per year.” (Water operator, Takeo)

Within this context, grants and technical assistance were viewed as essential for managing climate risk, while loan-based finance was seen as increasing financial vulnerability. This aligns with evidence that small water utilities in weak regulatory environments rely heavily on concessional finance due to limited capacity to absorb repayment risk ([6]; [15]).

Table 4. Water operators’ preferences for financing instruments by adaptation measure (RQ2).

Notestothetable: Rankings are based on a scenario-based preference-ranking exercise embedded within focus group discussions; Lower mean scores indicate stronger preference; Water operators and sanitation suppliers were presented with different adaptation options reflecting their service models; Water operators and sanitation suppliers were presented with the same financing instruments options.

Sanitation suppliers showed comparatively greater openness to government loans and government-guaranteed commercial loans, particularly for resilient latrine construction and related services (Table 5). Focus group discussions indicate that this reflects their need for working capital rather than large infrastructure investment, alongside narrower profit margins and demand volatility. As one supplier noted, droughts reduce household purchasing power and delay sanitation investments:

“When there is drought, people don’t think about latrines. They think about water, food, and daily survival. Only when they have extra money do they come back to us.” (Sanitation supplier, Kratie)

Smaller, family-run suppliers expressed reluctance to take on unguaranteed commercial loans, citing limited ability to absorb repayment risk, while larger suppliers were more open to loan finance if supported by subsidies or guarantees. These patterns are consistent with studies showing that sanitation enterprises face acute cash-flow constraints and high sensitivity to climate and income shocks ([22]; [10]; [20]).

These patterns align with the analytical framework for RQ2, which conceptualises financing preferences as responses to repayment risk, cost volatility, cash-flow constraints, and climate-linked demand uncertainty, rather than abstract preferences for specific financial instruments ([19]; [26]; [23]).

Table 5. Sanitation suppliers’ preferences for financing instruments by adaptation measure (RQ2).

Notestothetable: Rankings are based on a scenario-based preference-ranking exercise embedded within focus group discussions; Lower mean scores indicate stronger preference; Water operators and sanitation suppliers were presented with different adaptation options reflecting their service models; Water operators and sanitation suppliers were presented with the same financing instruments options.

To tighten integration between ranking results and qualitative evidence, Table 6 summarises the core coding outputs used to interpret financing preferences. Codes were developed around operating cost pressures, seasonal revenue volatility, governance-related cost burdens, working capital constraints, and repayment risk perception under climate stress.

Overall, the results indicate that financing preferences are shaped less by the novelty of instruments and more by suppliers’ exposure to climate risk, cost uncertainty, repayment constraints, and the degree to which financing arrangements reduce risk at the point of service delivery rather than shifting it onto small providers ([19]; [26]; [23]). The strong divergence between water operators and sanitation suppliers reflects fundamental differences in capital intensity, revenue structure, and risk-bearing capacity. For water operators, high capital intensity, rising operating costs, tariff constraints, and revenue volatility combine to make debt-financed investment particularly risky. Prior studies show that small water utilities in low-income contexts face increasing operating expenditures under climate stress, while weak regulatory environments and limited tariff flexibility constrain cost recovery ([6]; [15]). In such settings, concessional finance, grants, and technical assistance reduce downside risk and provide flexibility that commercial loans or bond-based instruments do not. The strong preference for donor-supported and concessional finance observed in this study is therefore consistent with recent evidence that small WASH providers rely on public and concessional support when exposure to climate risk, operating cost volatility, and governance constraints limits their ability to absorb repayment risk ([20]; [19]; [26]; [15]).

Table 6. Summary of coding outputs for RQ2.

Sanitation suppliers’ comparatively greater openness to loan-based finance reflects a distinct position within the rural WASH economy and contrasts sharply with water operators’ resistance to debt financing. While sanitation enterprises operate with lower capital intensity than water utilities, they face pronounced demand volatility and ongoing cash-flow constraints, particularly under climate stress. As [20] observed, financial risks in rural WASH are disproportionately borne by small-scale providers, many of whom lack the capacity to absorb repayment shocks or finance expansion under conditions of climate and demand uncertainty.

These constraints are compounded by lending conditions that are poorly aligned with WASH service delivery, including collateral requirements, high interest rates, and short loan tenors that do not match the long-term nature of water and sanitation investments ([16]). Within this context, sanitation suppliers’ preference for government-guaranteed or subsidised loans reflects a need for accessible and predictable working capital with risk-sharing, rather than a willingness to assume commercial debt. This pattern is consistent with evidence from Cambodia and other low-income settings, which identifies working capital constraints and income sensitivity as key barriers to scaling small-scale sanitation enterprises ([22]; [10]).

Across both supplier groups, the consistently low ranking of green bonds and social impact bonds reinforces the framework’s expectation that complex or financialised instruments are poorly aligned with the realities of small rural enterprises. As argued in the literature, such instruments often fail to reduce risk at the point of service delivery and may increase transaction costs without improving affordability or feasibility for local providers ([15]; [24]). These findings suggest that climate-resilient WASH financing must be differentiated by supplier type and grounded in supplier-level feasibility, rather than assuming a single financing pathway can effectively support both water and sanitation providers.

Across both water operators and sanitation suppliers, the preference-ranking exercise showed strong support for the principle of providing climate-resilient WASH services free of charge to poor households. When asked whether such services should be provided free of charge to poor households, 26 of the 27 suppliers responded affirmatively, while one water operator indicated uncertainty.

However, preferences shifted markedly when suppliers were asked to rank who should finance free provision (Table 7). Across both supplier groups, arrangements in which suppliers alone bore the cost were ranked lowest. By contrast, donor or philanthropic financing was ranked as the most acceptable option, while shared cost arrangements involving government were consistently preferred over supplier-only financing.

Table 7. Supplier preferences for financing free provision of climate-resilient WASH services to poor households.

Notestothetable: Rankings are based on a scenario-based preference-ranking exercise embedded within focus group discussions; Lower mean scores indicate stronger preference.

These findings align with the analytical framework for RQ3, which distinguishes between normative support for equity goals and the allocation of financial risk and responsibility in achieving those goals. To clarify the mechanisms underlying this divergence, Table 8 summarises the key coding outputs for RQ3.

Table 8. Summary of coding outputs for RQ3.

The qualitative evidence clarifies the distinction between normative endorsement of equity and rejection of supplier-funded cross-subsidisation. Suppliers emphasised that while free or heavily subsidised provision is necessary for poor households—particularly under climate stress—they lack the financial capacity to absorb these costs without external support. Sanitation suppliers were explicit about this constraint:

“We can’t give free latrines because we also need to cover our costs. If the government or NGOs share the cost, then we can help the poor.” (Sanitation supplier, Kampong Speu)

Suppliers also noted that poor households are least able to pay for resilient WASH services precisely during droughts or floods, when immediate survival needs take priority. However, this moral endorsement did not translate into willingness to absorb costs individually. Suppliers emphasised their limited margins and working capital constraints. Even where start-up costs were modest for sanitation businesses, liquidity remained tight, and free provision without cost-sharing was financially unviable. Suppliers repeatedly highlighted reliance on NGO programmes and subsidy schemes to reach poor households. One supplier noted that without NGO support, WASH programmes struggle to reach grassroots demand. At the same time, concerns about misallocation of “ID Poor” benefits and local-level discrimination underscored the need for transparent and accountable financing mechanisms ([20]).

These findings reflect well-documented constraints in rural WASH markets, including limited margins, high exposure to climate-related cost escalation, weak capacity for cross-subsidisation, and increasing risks associated with the financialisation of service delivery under climate stress ([22]; [20]; [15]; [23]). The preference for donor-funded or government-supported models is consistent with recent evidence that free provision in low-income and climate-vulnerable contexts is rarely sustainable without explicit public or concessional financing arrangements that prevent the costs of climate adaptation being transferred to small suppliers or poor households ([24]; [15]; [27]; [23]). [15] similarly cautioned that shifting the costs of climate adaptation onto suppliers or households’ risks deepening inequities rather than resolving them.

For sanitation suppliers in particular, shared financing arrangements reflect the interaction between income-elastic demand and climate stress. As documented in Cambodia and other low-income settings, sanitation investments are often postponed during periods of economic or climatic shock, making supplier-funded free provision especially risky ([10]; [22]).

Overall, the RQ3 findings reinforce the framework’s core proposition that equitable climate adaptation in WASH depends not only on recognising the need for free provision, but on explicitly allocating responsibility for financing it. Suppliers’ preferences indicate that climate-resilient WASH services for poor households are most feasible when financed through public and concessional sources, rather than through supplier-funded cross-subsidisation ([10]; [15]).