Assessing Uzhavar App Adoption Among Farmers Practicing Non-Chemical Agriculture: A Human-Computer Interaction Perspective Using Bayesian SEM and the Technology Adoption Model (TAM)

Abstract The Uzhavar (Farmers) App, launched by the Tamil Nadu Department of Agriculture and Farmers’ Welfare in 2018, has reached nearly one million downloads and serves as a vital digital resource for the state’s farming community. Designed to enhance access to agricultural information and facilitate the dissemination of knowledge, the app supports e-governance functions such as crop insurance, subsidies, on-farm engineering, and post-harvest management. Notably, it also provides information relevant to non-chemical agricultural methods (NCAM), including traditional seed storage and logistics.This study examines the adoption and usability of the Uzhavar App among farmers practising NCAM, utilizing the Technology Adoption Model (TAM) in combination with Bayesian Structural Equation Modelling (BSEM). Key objectives include assessing the impact of user interface (UI) design and atomic visual aesthetics (AVA) on utility perception, measuring user experience (UX), and identifying opportunities for UI/UX improvements. Exploratory Data Analysis (EDA) informs the structural model, while BSEM is employed to analyze causal relationships within the TAM framework. The findings offer insights into how digital technologies can foster rural development, promote technology acceptance, and support sustainable agricultural practices through inclusive, user-centred design.