Internet of things platforms adoption in agriculture: comparative theoretical models

Purpose: The purpose of this study is to determine the farmers’ behavioural intention (BI) to adopt Internet of things platforms (IoT-P) in the agriculture context by comparing two well-known theories: the united theory of acceptance and use of technology (UTAUT), and the decomposed theory of planned behaviour (DTPB) with the integration of innovation resistance theory (IRT). Design/methodology/approach: Purposive sampling was used to get responses from 267 potential farmers to examine their IoT-P adoption intention in Pakistan. The PLS-SEM, PLS model evaluation criterion and PLS model selection criterion were considered to determine the significance of path co-efficient, explanatory power, predictive power and more parsimonious model. Findings: The findings demonstrate that DTPB is the best model with the extension of functional barriers (FBs) and psychological barriers (PBs). It has more predictive relevance and explanatory power. The results show that farmers’ attitude (ATT), based on the evaluation of three attributes (i.e. perceived usefulness (PU), perceived ease of use (PEOU) and compatibility (COMP)), is the strong predictor of farmers’ BI to adopt IoT-P. In addition, self-efficacy (SEF) and facilitating conditions (FC) peer influence (PI) and superiors’ influence (SPI) are required for adoption of IoT-P devices. Finally, FB and PB significantly and negatively influence the farmers’ BI to adopt IoT-P. Originality/value: This research is the first to consider the two technology adoption models with the integration of IRT for explaining farmers’ BI in the context of agriculture.