Citation

Osrof, Hazem Yusuf and Tan, Cheng Ling and Yeo, Sook Fern and Tan, Kim Kua (2025) Unveiling the truth: are farmers ready for smart agriculture? Insights from a hybrid PLS-SEM-ANN approach. Journal of Modelling in Management. ISSN 1746-5664

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Abstract

Purpose Adopting smart farming technologies (SFTs) remains limited among farmers, especially in developing nations. While this is often attributed to resistance to technological change, farmers’ true technology readiness (TR) has been insufficiently explored. Moreover, existing research on TR’s antecedents has narrowly focused on demographic factors and past experiences, neglecting broader environmental influences. Therefore, this study aims to propose a novel framework grounded in the stimulus–organism–response (SOR) model, examining how various drivers and barriers shape farmers’ TR and, in turn, their intention to adopt SFTs. Design/methodology/approach Data were collected from 351 farmers and analyzed using a hybrid partial least squares (PLS)–structural equation modeling–artificial neural network (PLS-SEM-ANN) approach. This integrated method reveals linear and nonlinear interactions, offering deeper insights into the factors influencing TR and adoption intention. Findings Perceived efficiency, facilitating conditions and financial incentives substantially boost positive readiness (motivators), whereas perceived cost, complexity and uncertainty reinforce negative readiness (inhibitors). Motivators strongly predict farmers’ adoption intentions of SFTs, overshadowing any deterrent effect from inhibitors. The ANN analysis validated most PLS-SEM findings while offering deeper insights into the nuanced roles of cost and uncertainty in shaping negative readiness. These results challenge the notion that farmers are inherently resistant to innovation, suggesting that when supportive conditions exist, adoption likelihood increases significantly. Originality/value By extending the SOR model to the context of SFT adoption, this study is the first, to the best of the authors’ knowledge, to expand the scope of TR antecedents to include psychological and environmental factors. It also provides fresh evidence that fostering a positive, innovation-driven mindset is more impactful than merely reducing barriers.

Item Type:	Article
Uncontrolled Keywords:	Smart agriculture
Subjects:	S Agriculture > S Agriculture (General)
Divisions:	Faculty of Business (FOB)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 Sep 2025 09:11
Last Modified:	05 Oct 2025 16:51
URII:	http://shdl.mmu.edu.my/id/eprint/14627

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