IoT-Enabled Quality-Triggered Markdown Pricing for Perishable Food: Equity and Waste Implications

Area of Science:

• Operations Research
• Supply Chain Management
• Food Science

Background:

• Inequitable food access is exacerbated by delayed markdowns on perishables, increasing waste.
• Current markdown strategies limit affordability gains and fail to prevent spoilage.

Purpose of the Study:

• To examine how Internet of Things (IoT) real-time quality monitoring can optimize markdown strategies.
• To assess the impact of quality-triggered markdowns on food waste and food equity.

Main Methods:

• Developed an analytical pricing and markdown model for perishables with quality-sensitive demand.
• Compared optimal pricing decisions under IoT-enabled quality observability versus a baseline without IoT.
• Established convexity and derived closed-form solutions for optimal pricing and markdown parameters.

Main Results:

• Continuous quality visibility leads to earlier, deeper markdowns while product quality is still acceptable.
• Increased sell-through of products before they become unsalable.
• Quantified waste reduction and an expanded window for affordable purchases by price-sensitive consumers.

Conclusions:

• Proactive, quality-aligned pricing policies supported by IoT enhance food equity.
• Retailer profitability is maintained, demonstrating the economic viability of the approach.
• IoT integration offers a pathway to simultaneously reduce food waste and improve access to affordable nutrition.