2018
DOI: 10.1016/j.agsy.2018.09.007
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Representation of decision-making in European agricultural agent-based models

Abstract:  Agent-based modelling is a suitable tool for improving the understanding of farmers' behaviour.  Review 20 agricultural ABM addressing heterogeneous decision-making processes in the context of European agriculture.  Considerable scope to improve diversity in representation of decision-making by combining existing modelling approaches.  More coordinated and purposeful combinations of ABM and hybrid modelling approaches are needed.  Results provide an entry point for collaboration of agent-based modellers,… Show more

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Cited by 132 publications
(91 citation statements)
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References 119 publications
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“…The low influence of farm size, pig/poultry density, grassland density, and biotope index on the probability of crop cultivation in comparison with the soil variables can be explained by their low tendency to form spatial patterns or clusters in Lower Saxony, which is reflected in the high standard deviation values. In our analysis, we focused on environmental variables instead of economic variables because most of the studies concerning the cropping-plan decision making process of farmers consider economical and sociological drivers [3,61]. However, we could show the still high potential of soil variables as drivers for decision making, which is also confirmed by a study of Peltonen-Sainio et al [62].…”
Section: Reflections On the Methods Usedsupporting
confidence: 56%
“…The low influence of farm size, pig/poultry density, grassland density, and biotope index on the probability of crop cultivation in comparison with the soil variables can be explained by their low tendency to form spatial patterns or clusters in Lower Saxony, which is reflected in the high standard deviation values. In our analysis, we focused on environmental variables instead of economic variables because most of the studies concerning the cropping-plan decision making process of farmers consider economical and sociological drivers [3,61]. However, we could show the still high potential of soil variables as drivers for decision making, which is also confirmed by a study of Peltonen-Sainio et al [62].…”
Section: Reflections On the Methods Usedsupporting
confidence: 56%
“…Modelling in teractions by simulating material exchanges among economic agents in agro food networks is an approach that helps to design, quantify and assess the potential socioeconomic and ecological benefits of social change towards circular economy patterns (Elsawah et al, 2015;Filatova et al, 2013;Le Page et al, 2013). Agent based modelling is a particularly important as a tool that enables simulation of complex networks of agents in farming systems (Huber et al, 2018).…”
Section: Purposementioning
confidence: 99%
“…Concerning social simulation, imitating real world farmer choices can involve more complex decision making than in our simulated agents. More precisely, individual adaptation (Berger and Troost, 2014) and social learning (Huber et al, 2018), could potentially be included in FAN, for instance by allowing farms to alter land use or livestock populations in response to material availability in the network or after the alteration of global supply chains. d Lack of actual data to parametrize some key processes.…”
Section: Fan Evaluationmentioning
confidence: 99%
“…The question of how to represent decision-making is almost a perennial topic of discussion among those interested in ABM, and indeed boundedly and non-rational decision-making more generally (e.g. [83,84]), but Groeneveld et al [85] found most researchers in ABM of LUCC are still using utility maximization, whilst Huber et al [86] note a lack of consideration of values, norms and social interactions in ABMs of European agriculture. There are a plethora of theories and algorithms for implementing decision-making in specific and general contexts.…”
Section: Decision-makingmentioning
confidence: 99%