Optimizing strategies for e-waste supply chains under four operation scenarios.

Area of Science:

• Supply Chain Management
• Environmental Economics
• E-commerce

Background:

• Online recycling is a growing research area, but its service functions, like online promotion and offline collection, are understudied.
• Existing models often overlook the integration of service quality and recycling incentives.

Purpose of the Study:

• To analyze and compare four distinct online recycling channel models.
• To optimize service quality control and supply chain profits using game theory.
• To investigate the impact of recycling incentives and market demand on channel strategies.

Main Methods:

• Development of four recycling channel models: manufacturer (A), recycler (B), online (C), and manufacturer's platform (D).
• Application of game theory to derive profit functions and optimize strategies.
• Numerical simulation to analyze the effects of incentive limits and market demand.

Main Results:

• Model D (manufacturer's platform + recycling channel) offers superior consumer prices and service quality within a specific incentive range (λ∈(0,3)).
• Manufacturer and online platform profits in Model D show a peak relationship with the recycling incentive limit.
• Recycler profits consistently increase with the incentive limit, and supply chain profits rise with market size (D₀∈(0,100)).

Conclusions:

• The manufacturer's self-built platform model (D) demonstrates significant advantages in service quality and consumer benefits.
• Strategic management of recycling incentive limits and market demand is crucial for optimizing profits across the supply chain.
• Integrating online promotion with offline recycling functions enhances overall supply chain performance.