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Purpose This study fulfils the need by identifying the factors affecting the adoption of smart farming to understand the cause of low adoption despite having continuous support from the different emerging economies. Design/methodology/approach The study is exploratory in nature and positing a extended innovation diffussion model in the smart farming context. A total of 597 respondent's data is analysed using partial least square based structural equation modelling (PLS-SEM) technique. Findings The findings suggests that , Relative Advantage, Compatibility, Ease of use, Attitude, Agriculture Extention Communication effectiveness, and Government support positively influence the adoption of smart farming. At the same time, as we hypothesized, perceived risk negatively influences smart farming adoption. While Visibility and Result demonstrability do not influence smart farming adoption. In the case of Attitude, Relative advantage, Compatibility, Ease of Use, and Result demonstrability have a positive influence, and Compatibility and Visibility found to have no impact on Attitude. Research limitations/implications Though every effort has been made to have a substantial representation of each segment, though it is hard to have in limited time constraints. The generalization of the findings needs to be done with suitable caution. The data is cross-sectional, providing a future opportunity for upcoming scholars to bring some in-depth findings using qualitative techniques. The study has attempted to bring significant variables through SLR. However, there is a possibility to include several other variables like farmers' technical and managerial skills, experience in farming, impact of training programs etc. Since this study is conducted in one economy, India. Hence, the same factors should be tested in different socio-economic boundaries to bring generalizability. Practical implications The most important factor in the adoption of smart farming is Relative Advantage followed by attitude. It implies that the farmers or agricultural workers have a favorable opinion after using tech-enabled services. However, to maintain this continuous usage, the important factors influencing the Attitude are the relative Advantage, Ease of use, and result demonstrability. The innovation must be economic value adding, easy to understand and user-friendly, as most farmers are small-scale agricultural workers. Originality - The model under study is among few studies which posits a composition of psychological factors along with environmental (government support) and technological factors. The sample recruitment and selection is comprehensive to ensure the right representation of the target population. Overall the study is positing a strong model for future researchers to test this extended innovation diffussion model.