Modeling agricultural supply chain flexibility : a case study of cassava farming business in Thailand

Abstract

The logistics and supply chain management for agricultural supply chain in Thailand has been more emphasized by both private and public sectors due to its importance to the national economy. The key performance indicators of agricultural supply chain traditionally consider three major dimensions including cost, lead time, and reliability. However, the supply chain flexibility which is an important indicator to assess the ability of all players in the agricultural supply chain can accommodate the additional demand is rarely explored. The objective of this study is to develop a mathematical programming model to assess the supply chain flexibility for cassava business. In this study, a stochastic programming approach is adopted for modeling the flexibility. The proposed model was divided into two stages. The first stage (BASE) evaluates the demand base pattern along the cassava supply chain networks. The second stage (ADD-VOL) is to assess the reserve capacity using the base pattern obtained from the first stage. The reserved capacity at each stage presents the flexibility of the supply chain that can accommodate additional demand. The proposed models could be used to identify the bottlenecks of the supply chain in order to enhance its capacity for better serving the future supply and demand changes.