Abstract

This study estimates the economic value of smart water infrastructure using the contingent valuation method (CVM). A double-bounded dichotomous choice format was employed to assess household willingness to pay (WTP) for four digital water technologies, including pipeline digital twin, AI-based purification, treatment plant digital twin, and asset management systems. Based on a nationwide online survey of 1,400 respondents, a bivariate probit model was applied to jointly analyze sequential responses and to derive statistically valid WTP estimates. The analysis confirms that users assign substantial economic value to digital water technologies, suggesting strong consumer support for digital transformation in water services. These findings provide empirical justification for long-term infrastructure investment and offer practical implications for rate-setting and policy design that reflect public preferences and perceived benefits.