Summary
This quasi-experimental study evaluated the Mobile Agri Support Services (MASS) initiative—a 'phygital' model combining physical field demonstrations and digital advisory platforms—among 1,000 small and marginal farmers in three aspirational districts of Telangana, India. Using difference-in-differences regression over one year (June 2023–July 2024), the intervention achieved a substantial net increase of 78.11 units in attitude scores, with 80–90% of beneficiary farmers shifting to high-attitude categories compared to 88–92% of controls remaining in low-attitude categories. The findings suggest that bridging the last-mile delivery gap through integrated extension—combining mobile demonstrations, expert interaction, soil testing, and digital platforms—can overcome socio-economic and infrastructural barriers to technology adoption among marginalised farming populations.
Regional applicability
Whilst this study was conducted in India under specific socio-economic and infrastructural conditions in Telangana, the phygital service model and its emphasis on bridging last-mile extension delivery gaps may have limited direct transferability to United Kingdom farming contexts, where digital adoption, extension infrastructure and farmer literacy are considerably higher. However, the study's methodology and findings on the drivers of digital service acceptance (education, media exposure, decision-making behaviour) could inform UK policy on improving agricultural digital advisory uptake in less-connected or underserved farm communities.
Key measures
Farmer attitude scores (low vs. high categories), net increase in attitude scores (78.11 units), proportion of farmers shifting to high-attitude category, interaction effect significance (p<0.01), influence of education, extension participation, media exposure, risk-taking ability and decision-making behaviour on adoption
Outcomes reported
The study measured changes in farmer attitudes toward phygital (physical + digital) agricultural services before and after a one-year MASS intervention, using difference-in-differences analysis to quantify the net effect on adoption. It assessed socio-economic factors influencing acceptance of integrated mobile and in-person extension delivery.
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