Cohesion Model and Scenario Simulation for Risk Prevention of “Blockchain + Agriculture Crowdfunding†from the Synergistic Perspective

Ye Xue, Ying Li, Xiaodong Ji, Haodong Wu, Yue Wang and Sijian Zhao

SAGE Open, 2024, vol. 14, issue 4, 21582440241286587

Abstract: Aiming at the problems such as scattered subjects, static mode and single function, this paper explores a dynamic synergistic risk prevention mode of agricultural crowdfunding that adapts to the age of data intelligence. Based on multiple prevention subjects, the blockchain technology and cohesion principle are introduced into agricultural crowdfunding prevention, and then a risk prevention dynamic model of “blockchain + agricultural crowdfunding†is constructed from the synergistic perspective. Fuzzy cognitive map model and its reasoning mechanism are used to simulate four scenarios of 1-subject, 2-subjects, 3-subjects, and 4-subjects respectively in the dynamic model and the static model. The results show that: as the number of risk prevention subjects increases, so does the cohesion, and the cohesion of multi-subjects reaches a higher state in less time and the steady-state faster, even though the fluctuation range reduces. The risk value for the multi-agent reduces rapidly and reaches a lower risk value in a shorter period of time. Overall, cohesion increases while risk reduces. In the same scenario, dynamic mode cohesion is stronger than static mode cohesion, and it takes less time to attain the steady-state value. Under various scenarios, the dynamic model’s cohesiveness steady-state value increases with the number of subjects, which is stronger than the static model’s. This study not only enriches and develops the theory of risk management of agricultural crowdfunding, but also provides a decision-making basis for the enterprises and the government, etc., to formulate, adjust, and implement risk prevention measures.

Keywords: blockchain; agricultural crowdfunding; synergy; risk prevention dynamic model; fuzzy cognition map (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:14:y:2024:i:4:p:21582440241286587

DOI: 10.1177/21582440241286587

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