Adoption pathways for sustainable intensification technologies in the Indian Sundarbans: Combining web-based prediction and natural language processing

Enhancing resilience of resource-constrained smallholder farms in the climate-stressed Sundarbans necessitates evidence-based upscaling of sustainable intensification (SI) technologies. This study aims to enhance the resilience of resource-constrained smallholder farms in the climate-stressed Sundarbans by identifying pathways for evidence-based upscaling of sustainable intensification (SI) technologies. Focusing on salinity-tolerant paddy varieties (STPVs) and zero-tillage potato cultivation (ZTPC), demonstrated between 2022 and 2024, the research integrated quantitative adoption modelling with qualitative narrative analysis. Using the web-based Smallholder ADOPT model informed by focus group discussions and interviews, the study forecasted peak adoption levels (PAL) and time to peak adoption (TPA) under favorable and unfavorable conditions, alongside sensitivity analysis of adoption drivers. Under favorable scenarios, high PALs (96–98%) were predicted within 6–8 years, while unfavorable contexts produced variable PALs (2–98%) and longer TPAs (8–16 years). Key sensitive drivers included enterprise scale, profit advantage, trialing ease, skill levels, and financial constraints. Group-based elicitation yielded more optimistic adoption forecasts than individual interviews, reflecting collective learning and risk-sharing benefits. However, model-based predictions may overestimate adoption due to unaccounted local constraints. Narrative analysis, supported by NLP-driven text mining, confirmed concordance between model-identified and contextual drivers such as biophysical stress and storage limitations. The findings suggest that successful SI upscaling in fragile agroecosystems requires strengthening extension systems and farmer organizations, expanding land access, improving skills, and addressing financial and technological risks. Integrating quantitative prediction with qualitative insights provides a robust framework for understanding and enhancing technology adoption in climate-vulnerable smallholder settings