Farmer Adoption of Mobile Agriculture Applications: An Empirical Study of Adoption, Usage and Agricultural Decision-Making

Mobile technologies have created new opportunities for delivering agricultural information and services directly to farmers. Mobile agriculture applications can provide weather information, market prices, crop advisory, pest and disease information, financial services, and decision-support. Previous studies have identified both the potential of these applications and barriers to their adoption, including digital literacy, connectivity, language, usability, trust, device access, and data costs. However, the reviewed literature largely treats application functionality, smartphone adoption, and the broader mAgriculture ecosystem as separate areas of study. This paper proposes an empirical framework for examining how farmer-level and application-level factors influence initial adoption, actual usage, and continued use of mobile agriculture applications, and whether such usage contributes to improved agricultural decision-making. The proposed study focuses on the Indian context and considers digital literacy, perceived usefulness, perceived ease of use, trust, information quality, local-language availability, and usability as major explanatory factors. A structured questionnaire and quantitative analysis are proposed, supported by a formal measurement model, regression specifications, and mediation tests. The paper does not report fabricated survey results; instead, it provides a research framework that can be implemented through primary data collection.