The green transformation of production modes plays an essential role in the sustainable development of China’s agriculture and the modernization process, but there is often a deviation between farmers’ behavior and their willingness regarding green production. This paper analyzed the factors influencing the deviation of farmers’ green production behaviors from their willingness, along with their hierarchical logic structure, using the ordered logit model and ISM model with field survey data of 436 households in Hainan Province. The results show that: (1) there are deviations between farmers’ green production behavior and willingness; (2) age, number of dependents, peer influence, and social networks aggravate farmers’ green production behavior–willingness deviation, while ethnicity, education, land fragmentation, agricultural expenditure, land transfer, neighborhood learning, and green production cognition mitigate the deviation; (3) among the significant influencing factors, farmers’ perceptions of green production, peer influence, land transfer, and agricultural expenditure are the direct surface factors, while neighborhood learning, land fragmentation, and number of dependents are the middle indirect factors, and farmers’ education, social networks, age, and ethnicity are the deep-rooted factors. This study sheds more light and detail on the understanding of the factors influencing farmers’ green production behavior–willingness deviation, and provides more practical and relevant guidance for the agricultural green development in tropical China.

Exploring the determinants of residents’ willingness to pay (WTP) for water quality improvements is essential for protecting the water quality and formulating effective governance policies. This paper applies the double-bounded dichotomous contingent valuation method (CVM) to determine residents’ WTP for water quality improvements, calculate the average annual willingness of Haikou residents to pay for water quality improvements, and explore the factors influencing residents’ WTP for water quality improvements. Interpretive structural modeling (ISM) is then used to further analyze the association and hierarchy between the influencing factors. The results show that (1) Residents are willing to pay an average of 28.42 RMB/household/year for water quality improvements, and the total annual value of water quality improvements in Haikou is at least 5.58 × 10⁸ RMB; (2) age, education level, income level, minor family member and government trust are the main factors that significantly (p < 0.05) influence urban residents’ WTP; (3) among the factors identified as significantly affecting WTP, the deeper root factors include educational attainment, age, and ultimately, the willingness of residents to participate in water quality improvements through indirect factors (government trust, income level, presence of minors). This study allows an in-depth and detailed understanding of the determinants of residents’ WTP for water quality improvements and provides a practical and relevant guide to water quality improvements in the tropics.