Abstract
Thailand has been one of the largest natural rubber (NR) exporters in the world since 1991. However, the upstream rubber supply chain suffers from problems such as oversupply and decreasing price. This work proposed a decisionsupport model that combines System Dynamics and Agent-Based Modeling simulation while taking into account the relationship between NR price and planting rate per year, as well as between NR price and crude oil price. The input data between 2002 and 2015 included area sizes, tapping yield, planting rates, growth rates, and time to start or end tapping. The upstream rubber supply chain models were simulated from 2002 to 2021. The hybrid models in this study were validated by comparing between the simulated NR volume and actual values. The average Mean Absolute Percentage Error was 8.6%. The results of this work may be used by stakeholders in NR supply chains, such as in government agencies, to support their policy making.
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