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This study explores the factors influencing farmers' willingness to adopt Internet of Things (IoT) technologies in Ghana's agricultural sector, addressing a significant research gap by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to a demographic and geographical context that has been underexplored in existing literature. A quantitative, non-experimental correlational research design was employed, utilizing Structural Equation Modeling (SEM) to analyze data from 526 participants, including officers from the Ministry of Food and Agriculture and practicing farmers, selected through stratified random sampling. The findings reveal that Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), and Habit (HT) significantly predict Behavioral Intentions (BI) to adopt IoT. Contrary to some previous studies, Price Value (PV) did not emerge as a significant predictor, suggesting a potential need for further investigation in this area. This research is pioneering in applying the UTAUT2 framework to IoT adoption in Ghana's agricultural sector, contributing valuable empirical insights and highlighting new considerations, particularly regarding the roles of Social Influence and Price Value. The study's findings have practical implications for technology developers and agricultural stakeholders, offering guidance on key factors to consider when designing and implementing IoT solutions for farmers. Furthermore, the research has broader social implications, particularly in supporting community outreach and educational programs aimed at enhancing agricultural productivity and improving livelihoods in Ghana through technology adoption.
Antwi-Boampong et al. (Fri,) studied this question.