Cooperation and collapse in a communal livestock production SES model – A case from South Africa

Rasch, Sebastian; Heckelei, Thomas; Oomen, Roelof; Naumann, Christiane

doi:10.1016/j.envsoft.2014.12.008

Cited by 30 publications

(25 citation statements)

References 54 publications

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“…The scarcity of attempts to model aspects such as values or social interactions is somewhat in contrast to ABM in other regions and farming systems. For example, in the context of social interactions and neighbourhood effects and their influence on farmers' behaviour there exist various empirical and theoretical agent-based models (e.g., Bell et al, 2016;Caillault et al, 2013;Chen et al, 2012;Manson et al, 2016;Rasch et al, 2016;Sun and Müller, 2013). Also, with respect to decision-making rules, there seems to be greater variety outside the European context (e.g., Acevedo et al, 2008;Janssen and Baggio, 2016;Le et al, 2008;Le et al, 2012;Manson and Evans, 2007;Matthews, 2006;Rebaudo and Dangles, 2011;Schreinemachers andBerger, 2011, Berger et al, 2017).…”

Section: Types Of Decision-making Mechanisms In European Abmmentioning

confidence: 99%

Representation of decision-making in European agricultural agent-based models

Huber

Bakker

Balmann

et al. 2018

Agricultural Systems

126

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 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, agricultural systems modellers and social scientist.

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Section: Types Of Decision-making Mechanisms In European Abmmentioning

confidence: 99%

Representation of decision-making in European agricultural agent-based models

Huber

Bakker

Balmann

et al. 2018

Agricultural Systems

126

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“…Reciprocity is strongly affected by the trust an individual has because they expect others will reciprocate. In addition, the degree of reciprocity can differ according to the expectations of others in the community (i.e., community norm about a certain behavior) (Rasch, Heckelei, Oomen, & Naumann, 2016). Ostrom (2003) also suggests that an individual's interpretation of others' reputation can increase his/her trust and norms of the behavior, which all form his/her reciprocity, which eventually affects their behavioral intention to cooperate or collaborate.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Reputation, trust, and norms as mechanisms leading to academic reciprocity in data sharing: An empirical test of theory of collective action

Kim

2018

Proc. Assoc. Info. Sci. Tech.

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This research investigated how scientists' academic reputation, community trust, and norms regarding data sharing all influence their academic reciprocity in data sharing, which eventually leads to the scientists' data sharing intentions. This research employed Ostrom's (2003) theory of collective action to better understand scientists' data sharing behaviors from the perspective of cooperation in a community. This research empirically evaluated the research model and related hypotheses by using the Structural Equation Modeling (SEM) method on a total of 456 survey responses from biologists in the U.S. The results suggest that biologists' perceived academic reputation significantly increases their perceived community trust, norm of data sharing, and academic reciprocity. Along with perceived academic reputation, both perceived community trust and norms of data sharing also significantly increases biologists' academic reciprocity in data sharing. This research also found that biologists' academic reciprocity and norms of data sharing significantly affect their data sharing intentions. The results of this research show that the theory of collective action provides new insight to scientists' data sharing behaviors. These results suggest how we can facilitate scientists' data sharing behaviors within a research community by increasing academic reciprocity through the mechanisms of reputation, trust, and norm.

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“…Regarding beef cattle production, prior ABMs have been designed for disease prediction and control measures [25][26][27][28][29]. Other works have taken the cattle industry as a case study to analyze the risk management strategies in reaction to disease outbreaks, agricultural policy interventions, and market dynamics in social-ecological systems [30][31][32]. To the best of the authors' knowledge, few works have examined human behavioral changes on animal disease transmission.…”

Section: Introductionmentioning

confidence: 99%

Simulating human behavioral changes in livestock production systems during an epidemic: The case of the US beef cattle industry

et al. 2021

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Human behavioral change around biosecurity in response to increased awareness of disease risks is a critical factor in modeling animal disease dynamics. Here, biosecurity is referred to as implementing control measures to decrease the chance of animal disease spreading. However, social dynamics are largely ignored in traditional livestock disease models. Not accounting for these dynamics may lead to substantial bias in the predicted epidemic trajectory. In this research, an agent-based model is developed by integrating the human decision-making process into epidemiological processes. We simulate human behavioral change on biosecurity practices following an increase in the regional disease incidence. We apply the model to beef cattle production systems in southwest Kansas, United States, to examine the impact of human behavior factors on a hypothetical foot-and-mouth disease outbreak. The simulation results indicate that heterogeneity of individuals regarding risk attitudes significantly affects the epidemic dynamics, and human-behavior factors need to be considered for improved epidemic forecasting. With the same initial biosecurity status, increasing the percentage of risk-averse producers in the total population using a targeted strategy can more effectively reduce the number of infected producer locations and cattle losses compared to a random strategy. In addition, the reduction in epidemic size caused by the shifting of producers’ risk attitudes towards risk-aversion is heavily dependent on the initial biosecurity level. A comprehensive investigation of the initial biosecurity status is recommended to inform risk communication strategy design.

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Cooperation and collapse in a communal livestock production SES model – A case from South Africa

Cited by 30 publications

References 54 publications

Representation of decision-making in European agricultural agent-based models

Representation of decision-making in European agricultural agent-based models

Reputation, trust, and norms as mechanisms leading to academic reciprocity in data sharing: An empirical test of theory of collective action

Simulating human behavioral changes in livestock production systems during an epidemic: The case of the US beef cattle industry

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