Factors Influencing Revenue Collection for Preventative Maintenance of Community Water Systems: A Fuzzy-Set Qualitative Comparative Analysis
This study analyzed combinations of conditions that influence regular payments for water service in resource-limited communities. To do so, the study investigated 16 communities participating in a new preventive maintenance program in the Kamuli District of Uganda under a public–private partnership framework. First, this study identified conditions posited as important for collective payment compliance from a literature review. Then, drawing from data included in a water source report and by conducting semi-structured interviews with households and water user committees (WUC), we identified communities that were compliant with, or suspended from, preventative maintenance service payments. Through qualitative analyses of these data and case knowledge, we identified and characterized conditions that appeared to contribute to these outcomes. Then, we employed fuzzy-set qualitative comparative analysis (fsQCA) to determine the combinations of conditions that led to payment compliance. Overall, the findings from this study reveal distinct pathways of conditions that impact payment compliance and reflect the multifaceted nature of water point sustainability. Practically, the findings identify the processes needed for successful payment compliance, which include a strong WUC with proper support and training, user perceptions that the water quality is high and available in adequate quantities, ongoing support, and a lack of nearby water sources. A comprehensive understanding of the combined factors that lead to payment compliance can improve future preventative maintenance programs, guide the design of water service arrangements, and ultimately increase water service sustainability.
Open Access Status
Olaerts, Liesbet; Walters, Jeffrey; Linden, Karl G.; Javernick-Will, Amy; and Harvey, Adam, "Factors Influencing Revenue Collection for Preventative Maintenance of Community Water Systems: A Fuzzy-Set Qualitative Comparative Analysis" (2019). School of Engineering and Technology Publications. 440.