This paper aims to formulate a joint production and pricing model within a blockchain-enabled reverse logistics system. The authors’ analysis reveals that the optimal production quantity follows a benchmark-type policy: it decreases with the inventory level, while the optimal planned mean demand increases with inventory. These structural results are derived through theoretical analysis and further validated through numerical simulations.
This paper develops a joint production and pricing model in a blockchain-enabled reverse logistics system. The analysis reveals that the optimal production quantity follows a benchmark-style policy – decreasing with inventory – while the optimal planned mean demand increases with inventory. The authors examine how three blockchain-influenced factors – demand multiplier, demand variability and reverse logistics cost – affect firm decisions and expected profit.
Numerical results show that a higher demand multiplier enhances profitability and justifies greater production. In contrast, increased demand variability, as may arise from blockchain-induced uncertainty, reduces expected profit but leads to higher production as a hedge. Higher reverse logistics costs prompt the firm to reduce production, lowering profits.
Notably, the planned mean demand exhibits nonmonotonic behavior across these dimensions, reflecting the complex pricing trade-offs under blockchain dynamics. The findings highlight both the opportunities and operational risks introduced by blockchain.
This paper formulates a joint production and pricing model within a blockchain-enabled reverse logistics system. The authors analysis reveals that the optimal production quantity follows a benchmark-type policy: it decreases with the inventory level, while the optimal planned mean demand increases with inventory. These structural results are derived through theoretical analysis and further validated through numerical simulations.
