Integrating dynamic pricing strategies and demand-driven supply planning in wood pellet supply chains: A stochastic optimization approach

This study proposes a stochastic optimization model in wood pellet supply chains, integrating dynamic pricing strategies and demand-driven supply planning. In doing so, the correlation among supply, demand, pricing mechanisms, and profitability is analysed by implementing a Monte Carlo simulation approach with 10,000 iterations. Moreover, the seasonal demand fluctuations and production capacity constraints are considered in this model to provide a more realistic representation of market dynamics. To validate the model and show its applicability, the case study of a wood pellet supply chain in Quebec, Canada is considered. The results reveal a strong positive correlation between price and profit, indicating that approximately 71.6 % of the variance in profit can be explained by changes in price. The findings underscore the need for smart pricing strategies in the industry, as the model demonstrates the certainty in supply chain profitability across all simulated scenarios. Furthermore, the optimization model improves the profitability by leveraging economies of scale in transportation. The proposed approach serves as a robust decision-support tool for strategic planning in the wood pellet industry incorporating complex market dynamics.