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Home▶ Journals▶ Indian Journal of Extension Education▶Archive▶Vol. 62 No. 4 (2026)▶Drivers of Farmers’ Intention to Adopt Digital Platforms…
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Research Article

Drivers of Farmers’ Intention to Adopt Digital Platforms for Natural Farming Inputs in Andhra Pradesh

,
Aravind Kumar Saride — Research Scholar
Mrigank Sharad — Assistant Professor, Rajendra Mishra School of Engineering Entrepreneurship, Indian Institute of Technology, Kharagpur, West Bengal, India
Published 28 Sep 2026 Vol. 62 No. 4 (2026), pp. 207-213 ● Open access
❝ How to cite 🔗 https://doi.org/10.48165/IJEE.2026.62430
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Abstract

The study examined the drivers of farmers’ intention to adopt a Natural Farming digital input platform. The Unified Theory of Acceptance and Use of Technology was extended by incorporating Personal Innovativeness, Perceived Cost and Perceived Risk alongside Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions. Primary data were collected between July and November 2024 from 795 Natural Farming farmers across Andhra Pradesh, employing a structured questionnaire through direct interviews and supported by Rythu Sadhikara Samstha, the state nodal agency for Natural Farming. An integrated methodology combining a two-stage Partial Least Squares Structural Equation Modelling with an Artificial Neural Network approach, complemented by Importance Performance Map Analysis, was employed. Results showed a positive and significant influence of Personal Innovativeness, Performance Expectancy, Effort Expectancy and Facilitating Conditions on behavioural intention, explaining 51.8% of its variance, while Social Influence, Perceived Cost and Perceived Risk were statistically non-significant. The Artificial Neural Network sensitivity analysis confirmed Personal Innovativeness as the most important predictor. Strengthening rural digital infrastructure and designing intuitive regional-language interfaces could accelerate inclusive adoption intention among small and marginal farmers.

KeywordsNatural farmingBehavioural intentionUnified theory of acceptance and use of technologyStructural equation modellingArtificial neural network

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