Taheri, Fatemeh, Marijke D’Haese, Dieter Fiems, Gholam Hossein Hosseininia, & Hossein Azadi (2020, October). Wireless sensor network for small-scale farming systems in southwest Iran: Application of Q-methodology to investigate farmers’ perceptions. Computers and Electronics in Agriculture, 177, art. 105682. (doi: 10.1016/j.compag.2020.105682) (Link: https://doi.org/10.1016/j.compag.2020.105682)
Abstract: The application of wireless sensor networks (WSNs) has been promoted worldwide as an approach to smart farming, sustainable resource management and improved crop productivity. Despite their promotion, WSNs are not widely adopted in the whole world, especially by small-scale farmers. The adoption of WSN technologies is strongly affected by the perceptions of farmers who are the main users and potential adopters of such technology. Yet, the way WSN technology is perceived has been poorly studied. This study aims at closing this gap by investigating the small-scale farmers’ perception regarding the application of WSNs for farming systems in Khuzestan Province, Iran. This research employed Q-methodology, an approach that integrates both qualitative and quantitative data allowing to study individuals’ subjective understandings of a specific topic. The Q-sort procedure was performed in the field with twenty-five small-scale cereal farmers (with less than 2 ha of land). Next Q-factor analyses were conducted using the PQMethod software. Results propose to group farmers along with four types of perceptions regarding the application of WSNs, namely support-seekers, resistance-adherents, optimists and adoptive-adherents. These four groups cover 67% of the variance across perceptions. Various perceptions have shown that farmers have different views on WSN applications. Awareness of these perceptions can provide a valuable frame for policy and decision-makers, and allow for addressing the farmers’ concerns and for developing appropriate and specific strategies for each group.
Fatemeh Taheri <email@example.com> is in the Department of Agricultural Economics, Ghent University, Ghent, Belgium.