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Development of horizontal coordination mechanisms for planning agricultural production

Description

Agricultural supply chains are complex systems which pose significant challenges beyond those of traditional supply chains. These challenges include: long lead times, stochastic yields, short shelf lives and a highly

Agricultural supply chains are complex systems which pose significant challenges beyond those of traditional supply chains. These challenges include: long lead times, stochastic yields, short shelf lives and a highly distributed supply base. This complexity makes coordination critical to prevent food waste and other inefficiencies. Yet, supply chains of fresh produce suffer from high levels of food waste; moreover, their high fragmentation places a great economic burden on small and medium sized farms.

This research develops planning tools tailored to the production/consolidation level in the supply chain, taking the perspective of an agricultural cooperative—a business model which presents unique coordination challenges. These institutions are prone to internal conflict brought about by strategic behavior, internal competition and the distributed nature of production information, which members keep private.

A mechanism is designed to coordinate agricultural production in a distributed manner with asymmetrically distributed information. Coordination is achieved by varying the prices of goods in an auction like format and allowing participants to choose their supply quantities; the auction terminates when production commitments match desired supply.

In order to prevent participants from misrepresenting their information, strategic bidding is formulated from the farmer’s perspective as an optimization problem; thereafter, optimal bidding strategies are formulated to refine the structure of the coordination mechanism in order to minimize the negative impact of strategic bidding. The coordination mechanism is shown to be robust against strategic behavior and to provide solutions with a small optimality gap. Additional information and managerial insights are obtained from bidding data collected throughout the mechanism. It is shown that, through hierarchical clustering, farmers can be effectively classified according to their cost structures.

Finally, considerations of stochastic yields as they pertain to coordination are addressed. Here, the farmer’s decision of how much to plant in order to meet contracted supply is modeled as a newsvendor with stochastic yields; furthermore, options contracts are made available to the farmer as tools for enhancing coordination. It is shown that the use of option contracts reduces the gap between expected harvest quantities and the contracted supply, thus facilitating coordination.

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Date Created
  • 2015