Optimizing Discount Offers in Online Retail Marketplaces: Roles of Inventory and Goodwill Dynamics

Abstract

Discount pricing plays a crucial role in enhancing competitiveness in e-commerce. However, the optimization of discount decisions within e-marketplaces has received limited attention. Specifically, theoretical gaps exist in analyzing discount pricing decisions with respect to dynamic system states and supplier-e-retailer interactions. This study addresses these gaps by proposing a dynamic, coordinated discount pricing approach for e-marketplaces, incorporating key system state measures—inventory and reputation. By utilizing a combined coordination-dynamic game model, our approach extends existing discount pricing frameworks into a structured and adaptive discount pricing strategy, offering practical insights for suppliers and e-retailers to enhance economic performance. We demonstrate that optimizing discounts within an adaptive framework with a coordinated focus on inventory and reputation reduces inventory shortages significantly (by 18% –24% ) and enhances goodwill (by 3.5% ), aligning with the key objectives of improving efficiency and responsiveness in technologically integrated supply chains. We further validate our findings through robustness checks, including stability testing, a comparison of stockout levels under dynamic and static discount pricing, and sensitivity analyses on demand volatility, confirming the model's reliability across varying conditions.