Smart Farming Technology Adoption Models to Improve Productivity and Water Efficiency
Keywords:
Smart Farming Technology, Technology Adoption, Water Efficiency, Agricultural ProductivityAbstract
This study aims to explore smart farming technology adoption models for improving agricultural productivity and water efficiency. The issue was examined because many smallholder farmers still face limited capital, low digital literacy, uncertain water availability, and uneven access to technical support. This study used a qualitative case study approach to understand farmers’ experiences, meanings, and decision-making processes in adopting smart farming technologies. Data were collected through semi-structured interviews, field observation, and documentation involving farmers, agricultural extension officers, farmer group leaders, irrigation actors, and technology facilitators selected through purposive and snowball sampling. The data were analyzed using thematic analysis supported by source triangulation, method triangulation, member checking, and audit trail procedures. The findings show five main themes: perceived usefulness for water efficiency, productivity as the main adoption motive, cost and technical skill as adoption barriers, social influence and extension support, and partial adaptive adoption. The study found that farmers did not simply accept or reject smart farming. They adjusted technology based on land size, crop type, water access, financial capacity, and local farming routines. These findings contribute to technology adoption theory by showing that smart farming adoption is a contextual social process, not only an individual technological decision. The study implies that policy and practice should support affordable technology, farmer-centered training, demonstration plots, and stronger institutional assistance. Future research should test adaptive adoption models across different agricultural contexts.
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