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Stream/Area:
-
Subject:
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Paper ID:
IJSREM66730
Volume:
10 |
8 |
Aug 2026
Pages:
1-23
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

PG Department of Commerce
Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), Chennai
PG Department of Commerce
Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), Chennai
PG & Research Department of Commerce
Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), Chennai
PG Department of Commerce
Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), Chennai
PG& Research Department of Commerce
Guru Nanak College (Autonomous), Chennai
Smart agricultural technologies such as mobile advisory applications, Internet of Things (IoT) sensors, and unmanned aerial vehicles (UAVs) hold considerable promise for improving farm productivity and resource efficiency, yet their adoption among farmers remains uneven. Drawing on an integrated Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT2) framework, this study examines the influence of farmers' perception, perceived usefulness, perceived benefit, effort expectancy, performance expectancy, social influence, and facilitating conditions on the adoption of smart agricultural technologies, and evaluates the mediating role of social media engagement in this relationship. Primary data were collected from 102 farmers using a structured Likert-scale questionnaire and analysed using descriptive statistics, Pearson correlation, and multiple linear regression. The results indicate that facilitating conditions and social influence are the strongest direct predictors of technology adoption, that perceived benefit and facilitating conditions most strongly predict social media engagement, and that effort expectancy and prior technology adoption significantly predict farmers' intention to use smart technologies. Social media, while strongly and positively correlated with adoption, did not emerge as a statistically significant independent predictor once facilitating conditions and social influence were accounted for, suggesting its role operates largely through its shared variance with these enabling conditions rather than as an independent driver. The findings offer practical guidance for policymakers, agricultural extension agencies, and agri-tech firms seeking to design infrastructure-linked, socially embedded interventions that accelerate the adoption of smart agricultural technologies.
KEYWORDS
This study set out to examine the effect of farmers' perception on smart agricultural technology adoption and to assess the mediating role of social media in that relationship, using primary data from 102 farmers analysed through descriptive statistics, correlation, and multiple regression. The findings show that facilitating conditions and social influence are the most consistent and statistically significant drivers of both technology adoption and social media engagement, while farmers' general perception and perceived usefulness carry limited independent explanatory power once these enabling factors are accounted for. Social media engagement, while strongly correlated with adoption, is better understood as sharing common antecedents with adoption, principally facilitating conditions and perceived benefit, than as an independent causal mediator. These findings offer a more infrastructure- and community-centred picture of smart agricultural technology adoption than purely attitudinal models would suggest, and they carry direct implications for how policymakers, extension agencies, and agri-tech firms should sequence their interventions to accelerate the transition toward sustainable, technology-enabled farming.
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Publication Date
8/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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