Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework

Huber, Robert; Xiong, Hang; Keller, Kevin; Finger, Robert

doi:10.1111/1477-9552.12447

Cited by 23 publications

(30 citation statements)

References 124 publications

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“…With the integration of learning in the SECLAND ABM, we build on the two essential factors of the decision-making process: the farming style symbolizing the intrinsic motivation of farmers, and well-being (a balance between income and workload). It is common in agent-based modeling to address risk-related adaptation of an agent through imitation or orientation within its social network (van Duinen et al 2016 ; Amadou et al 2018 ; Gawith et al 2020 ; Zagaria et al 2021 ; Marvuglia et al 2022 ; Huber et al 2022 ). However, this acknowledges only on the social aspect of learning, while the SECLAND ABM integrates learning as socio-ecological process that builds on the farming style and the occurrence of the extreme events.…”

Section: Discussionmentioning

confidence: 99%

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Effects of extreme events on land-use-related decisions of farmers in Eastern Austria: the role of learning

Egger,

Mayer,

Bertsch-Hörmann

et al. 2023

Agron. Sustain. Dev.

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European farm households will face increasingly challenging conditions in the coming decades due to climate change, as the frequency and severity of extreme weather events rise. This study assesses the complex interrelations between external framework conditions such as climate change or adjustments in the agricultural price and subsidy schemes with farmers’ decision-making. As social aspects remain understudied drivers for agricultural decisions, we also consider value-based characteristics of farmers as internal factors relevant for decision-making. We integrate individual learning as response to extreme weather events into an agent-based model that simulates farmers’ decision-making. We applied the model to a region in Eastern Austria that already experiences water scarcity and increasing drought risk from climate change and simulated three future scenarios to compare the effects of changes in socio-economic and climatic conditions. In a cross-comparison, we then investigated how farmers can navigate these changes through individual adaptation. The agricultural trajectories project a decline of active farms between −27 and −37% accompanied by a reduction of agricultural area between −20 and −30% until 2053. The results show that regardless of the scenario conditions, adaptation through learning moderates the decline in the number of active farms and farmland compared to scenarios without adaptive learning. However, adaptation increases the workload of farmers. This highlights the need for labor support for farms.

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Section: Discussionmentioning

confidence: 99%

“…Farms are exposed to several risks such as environmental, production, market, price, and political risks (Bard and Barry 2001 ; Huber et al 2022 ). Subsidy schemes as well as market demand for agricultural products and prices are external factors in the SECLAND model.…”

Section: Methodsmentioning

confidence: 99%

Effects of extreme events on land-use-related decisions of farmers in Eastern Austria: the role of learning

Egger,

Mayer,

Bertsch-Hörmann

et al. 2023

Agron. Sustain. Dev.

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“…The agent-based model (ABM) is a method developed based on the complex adaptive system, which could capture these iterations [ 54 , 64 ]. It simulates each agent from the bottom up by endowing the micro-subject with certain attributes, behavior rules, and interaction mechanisms to study the phenomenon at the macro-level [ 65 , 66 ]. To observe the influences of the social networks and social trust of farmers, we developed the ABM model with the Net logo 6.2.1 software.…”

Section: Methodsmentioning

confidence: 99%

Considering Farmers’ Heterogeneity to Payment Ecosystem Services Participation: A Choice Experiment and Agent-Based Model Analysis in Xin’an River Basin, China

Hui

Jin

et al. 2022

IJERPH

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The concept of watershed ecological compensation is one payment for ecosystem services (PES) program that incentivizes stakeholders undertake environmental conservation activities that improve the provision of ecosystem services. Defining the heterogeneity of farmers’ willingness to participate in watershed ecological compensation is critically important for fully understanding stakeholders’ demands. Accordingly, we designed a choice experiment survey to analyze the heterogeneity of policy preferences and willingness to receive compensation between upstream and midstream farmers in Xin’an River basin, China. Moreover, we simulated the impact of farmers’ social capitals’ heterogeneity with an agent-based model. The results show that there are significant differences in the preferences of agricultural waste recycling rate and agricultural water quality between farmers in the upstream and midstream. The total willingness of farmers in the upstream and midstream to participate in ecological compensation are RMB 149.88 (USD 22.54)/month and RMB 57.40 yuan (USD 8.63)/month, respectively. Social network size has a negative effect on farmers’ willingness to participate the programs. Our findings suggest that the characteristics of farmers’ influence their willingness to participate in the PES program. The results of this research can be used to improve PES management policies in the future, as well as to support sustainable environmental development and rural revitalization.

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“…Especially, farmers' land-use decisions are essential to be accounted for in developing more realistic scenarios (Huber et al, 2018). Agent-based modeling (ABM) has been widely used in land-use models to support policy analysis and planning (Parker et al, 2003;Huber et al, 2018Huber et al, , 2021. It seems that ABM is the most suited approach to simulate the environmental impacts of a complex and dynamic system accounting for the heterogeneous individual behavior of adapting, reacting, and interacting fields (Liu et al, 2015;Castro et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Coupling agent-based modeling with territorial LCA to support agricultural land-use planning

Ding

Achten

2022

Journal of Cleaner Production

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Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Cited by 23 publications

References 124 publications

Effects of extreme events on land-use-related decisions of farmers in Eastern Austria: the role of learning

Effects of extreme events on land-use-related decisions of farmers in Eastern Austria: the role of learning

Considering Farmers’ Heterogeneity to Payment Ecosystem Services Participation: A Choice Experiment and Agent-Based Model Analysis in Xin’an River Basin, China

Coupling agent-based modeling with territorial LCA to support agricultural land-use planning

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