Factors underlying farmers' intentions to adopt best practices: The case of paddock based grazing systems

John J. Hyland, Kevin Heanue, Jessica McKillop and Evgenia Micha

Agricultural Systems, 2018, vol. 162, issue C, 97-106

Abstract: The Irish beef sector is expected to increase output as part of the most recent national agriculture strategy. General improvements in pasture production efficiency can be achieved by increasing grass utilisation. However, Irish beef production is primarily based on extensive pastoral grazing with low uptake of best management practices among farmers. An important step in facilitating innovation in the sector is to gain improved understanding of the innovative behaviour of farmers. Hence, this study uses psychological constructs to analyse factors that affect the adoption of paddock based grazing systems by Irish beef farmers (n = 382). Farmers were surveyed from different regions within Ireland and Principal Component Analysis used to empirically confirm the hypothesised Theory of Planned Behaviour (TPB) constructs. Cluster analysis was thereafter employed as classification criteria to cluster respondents into types. The TPB was subsequently applied to explain intention to implement the grazing practice. Three clusters of farmers were elicited based on their beliefs of paddock based grazing systems and labelled The Engaged, The Restricted, and The Partially Engaged. The Restricted cluster was particularly unlikely to uptake the grazing practice as they perceived they lacked the required resources to implement the innovation. This was of particular relevance as the practice can be implemented with relatively few resources and therefore signals a knowledge gap. The findings are relevant to policy as they provide insights on the factors influencing the process of targeting knowledge transfer through appropriate channels which can help build potential drivers for behavioural change.

Keywords: Beef farmers; Rotational grazing; Innovation; Theory of planned behaviour; Resources (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (22)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:162:y:2018:i:c:p:97-106

DOI: 10.1016/j.agsy.2018.01.023

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