Revenue vs. Welfare: A Comprehensive Analysis of Strategic Trade-offs in Online Food Delivery Systems

TL;DR

This paper analyzes the strategic trade-offs between maximizing short-term revenue and optimizing long-term social welfare in online food delivery platforms through static and dynamic models, supported by simulations.

Contribution

It introduces a dynamic modeling framework that captures long-term effects and derives strategies balancing revenue and welfare in online food delivery systems.

Findings

GMV-focused strategies yield quick gains but harm long-term stability

Social welfare strategies lead to more sustainable outcomes

Simulations validate theoretical predictions of trade-offs

Abstract

This paper investigates the trade-off between short-term revenue generation and long-term social welfare optimization in online food delivery platforms. We first develop a static model that captures the equilibrium interactions among restaurants, consumers, and delivery workers, using Gross Merchandise Value (GMV) as a proxy for immediate performance. Building on this, we extend our analysis to a dynamic model that integrates evolving state variables,such as platform reputation and participant retention-to capture long-term behavior. By applying dynamic programming techniques, we derive optimal strategies that balance GMV maximization with social welfare enhancement. Extensive multi-agent simulations validate our theoretical predictions, demonstrating that while a GMV-focused approach yields strong initial gains, it ultimately undermines long-term stability. In contrast, a social welfare-oriented strategy produces more sustainable and robust outcomes. Our findings provide actionable insights for platform operators and policymakers seeking to harmonize rapid growth with long-term