Farm mechanization can promote the economic sustainability of small farms and in the context of cereal-legume systems strengthen plant protein-based diets, which support human health and environmental sustainability. However, mechanization inevitably displaces hired laborers who depend on manual farm work for their income. Few studies have systematically analyzed the differential effects on women and men hired labor. Here, we use primarily qualitative data from Myanmar and Bangladesh to test the hypothesis that the effects of mechanizing mung bean harvesting—which is now commencing in both countries—are likely to weaken women hired workers’ economic and personal empowerment. We focus on rural landless women laborers as an important part of the agricultural labor force. The results broadly confirm the hypothesis, although there is variation between the research sites. Harvesting mung beans is the only fieldwork task available to many landless women, particularly married women with children, in both countries. Gendered restrictions on women’s mobility and their role as family caregivers, as well as norms about appropriate work for women and men, restrict women’s options regarding alternative work both locally and further away. The effects are likely to be particularly negative in locations with minimal off-farm economic diversity and more restrictive gender norms. Overall, men across all sites will be less affected since their participation rates in harvesting and post-harvest processing are low. They are less restricted by gender norms and can travel freely to find work elsewhere. However, women and men in low asset households will find it problematic to find alternative income sources. Less restrictive gender norms would help to mitigate the adverse effects of farm mechanization. It is important to invest in gender transformative approaches to stimulate change in norms and associated behaviors to make a wider range of choices possible.

Agricultural mechanization has spread across much of Asia since the 1960s. It has increased agricultural productivity and reduced arduous farm work. However, differing impacts for smallholders and hired laborers, and for men and women, require careful consideration. This study analyzed, ex-ante, the likely social and economic tradeoffs of mechanizing the mungbean harvest in Bangladesh and Myanmar. We used a mixed methods approach combining survey data from 852 farm households with in-depth interviews in four villages. Partial budget analysis shows that mechanical harvesting of mungbean is not yet profitable for most farms. There is nevertheless an incentive to mechanize as the associated timeliness of the harvest reduces the risk of harvest losses from weather shocks. Men and women farmers expect time savings and reduced drudgery. The results confirm that hired workers depend on manual harvesting for income and status in both countries. Most hired workers are landless married women with limited access to other sources of income. In the short term, farmers are likely to combine manual harvests and a final mechanized harvest of the indeterminate crop. This could mediate the impact on hired workers. However, in the long term, it will be necessary to facilitate income-generating opportunities for women in landless rural families to maintain their well-being and income.

Floating agriculture transforms marshy lands into productive resources, enhancing food security and rural incomes in climate‐vulnerable areas. While prior research highlights its potential as a climate‐resilient practice, gaps remain in understanding the determinants of adoption and long‐term livelihood impacts. Our study addresses these gaps by examining farming procedures, profitability, impacts, and the key drivers and challenges influencing floating agriculture adoption in southern Bangladesh. Data was collected from 158 farmers using a pre‐tested questionnaire between October 2018 and April 2019. Profit function and logit regression models were applied to analyze profitability and socio‐economic determinants, complemented by qualitative methods and causal loop diagrams to assess impacts. Findings reveal that farmers employ both intercropping and monocropping, with a preference for seedling raising (156.37 USD/100 m²) over vegetable cultivation (121.56 USD/100 m²) due to higher profitability. Despite its labor‐intensive nature (73% labor costs for seedling rising vs. 85% for vegetable cultivation), floating agriculture boosts household income, meets local vegetable demand, and reduces reliance on external markets during shocks. Additionally, it provides ecological benefits such as waterweed management and reduced environmental pollution. Floating agriculture also alleviates poverty by enhancing agricultural production and generating a positive feedback loop of increased income, food availability, and improved nutrition and health. Adoption is influenced by age, experience, family size, income diversity, credit access, extension services, and market proximity. However, high capital costs, limited credit, market volatility, and biotic/abiotic stresses pose challenges. To scale up floating agriculture, policy measures should focus on financial support, technical training, cost‐effective innovations, and fostering cooperative farming. Institutional backing is crucial for promoting this sustainable cleaner production practice in flood‐prone regions of Bangladesh and similar global contexts.

Flash floods represent a major threat to agricultural production in Bangladesh's haor ecosystems, making timely harvesting essential for reducing crop losses and strengthening climate resilience. This study examines how livelihood heterogeneity influences combine harvester adoption and mechanization pathways under flood risk. Using survey data from 360 farm households across the haor districts of Sunamganj, Kishoreganj, and Netrakona, principal component analysis was employed to construct multidimensional livelihood and adaptation indicators, which were subsequently used in cluster analysis to identify livelihood typologies. Binary logit and multinomial logit models were then estimated to assess the relationship between livelihood heterogeneity and combine harvester adoption pathways. The analysis identified four distinct livelihood typologies, namely diversified asset holders, knowledge‐driven adaptive smallholders, networked flood‐resilient adopters, and resource‐constrained flood‐vulnerable traditionalists. Binary logit estimates confirmed significant livelihood heterogeneity in adoption, with predicted probabilities of 0.935, 0.931, 0.760, and 0.133 across the four livelihood typologies, respectively. The multinomial logit analysis further revealed that education level, extension contact, farmer‐group participation, cultivation intensity, and proactive flood‐adaptation practices significantly increased the likelihood of belonging to high‐adoption livelihood pathways, whereas resource constraints and weak institutional engagement were associated with low‐adoption pathways. This study advances the mechanization and climate adaptation literature by explicitly linking livelihood heterogeneity to combine harvester adoption under flood risk. The findings demonstrate that combine harvester adoption is embedded within broader livelihood configurations and functions not only as a labor‐saving technology but also as a climate‐risk management strategy. The findings highlight the need for livelihood‐specific policies that strengthen institutional support, improve access to mechanization services, and enhance the adaptive capacity of vulnerable farmers in flood‐prone environments.