Joint Pricing and Innovation Control in Regulated Recycling-Rate Diffusion

TL;DR

This paper models the joint control of pricing and innovation in recycling using a stochastic diffusion framework, incorporating regulations and analyzing the resulting control problem via HJB equations.

Contribution

It introduces a regulated stochastic diffusion model for recycling and formulates a joint control problem with rigorous HJB analysis and numerical validation.

Findings

HJB equation characterizes the optimal control policy.

Numerical experiments demonstrate the model's tractability.

Sensitivity analysis highlights parameter impacts on policies.

Abstract

We introduce a regulated stochastic diffusion model for the recycling rate and formulate a joint control problem over production and process innovation via the dynamics of recycling investment and product pricing. The resulting stochastic control problem captures the system manager's trade-off between product-price decisions and investment expenditures under an infinite-horizon discounted cost structure. Owing to the recycling-rate specification, we incorporate two regulated state processes, which induce additional policy-driven cost components in the value function consistent with green-economy regulations. We resolve the jointly regulated stochastic production and process-innovation admission control problem by introducing the associated Hamilton-Jacobi-Bellman (HJB) equation and providing rigorous proofs that establish the correspondence between the HJB solution and the value function of the underlying control problem. The HJB equation is analyzed under mild, practically motivated assumptions on the system parameters. We further present numerical experiments and sensitivity analyses to illustrate the tractability of the HJB characterization and to assess the practical relevance of the imposed parameter conditions.