Determinants of modern agricultural machinery adoption in Northern Bangladesh: A multivariate probit analysis

Farm mechanization is expanding in Bangladesh, yet smallholders continue to face constraints such as fragmented landholdings, high machinery costs, limited access to custom hiring services, and insufficient training. This study examines these challenges using secondary data from 5053 households in the Eastern Gangetic Plains collected under the Sustainable and Resilient Farming Systems Intensification project. Although the dataset emphasizes conservation agriculture and contains few machine-specific variables, it remains appropriate for assessing technology adoption in smallholder systems. A subsample of 1761 farmers from Rajshahi and Rangpur districts of Bangladesh was analyzed to assess the joint adoption of four modern machines: the rotavator, laser land leveler, happy seeder, and combine harvester. Unlike studies that consider single technologies, this research investigates how farmers’ adoption decisions interact. The descriptive statistics reveal that 56.8 % of households adopted the rotavator, whereas adoption of the other machines remained below 2.5 %. Multivariate Probit model identified that household size, family labor, off-farm income, machinery ownership, and institutional support generally encouraged adoption, while age, education, and limited familiarity with machinery reduced uptake for some technologies. Correlation results reveal both complementarities and substitution among machines. The findings underscore the need for targeted financial support, training, custom hiring services, and awareness programs to promote inclusive, region-appropriate mechanization. The study adds new empirical evidence by jointly analyzing multiple mechanization choices and clarifying the behavioral and structural conditions needed for sustainable agricultural intensification in smallholder systems.