O2O Food Delivery Pricing Strategy Analysis with Game-Theoretic Model

This dataset accompanies a research paper analyzing pricing strategies for Online-to-Offline (O2O) food delivery supply chains under anti-food waste regulations. The paper uses a game-theoretic model comparing uniform and differentiated pricing under consumer appetite and value heterogeneity. It provides a quantitative framework for analyzing merchant profit, consumer demand, and waste reduction.

Use Cases

• Analyze the impact of regulatory stringency on online and offline prices within the game-theoretic model.
• Compare uniform versus differentiated pricing strategies under varying consumer appetite structures.
• Model the effect of a higher share of small appetite consumers on prices under lenient versus strict anti-food waste rules.
• Examine how the degree of differentiation in perceived value between consumer types influences supply chain alignment on pricing.

Strengths

• The dataset is associated with a peer-reviewed research paper published on figshare.
• The analysis is grounded in a formal game-theoretic model with a restaurant and a platform.
• The dataset is openly available under a CC BY 4.0 license.

Limitations

• The dataset is a 227.5 KB DOC file, indicating it is likely a document describing the model and results rather than a structured, machine-readable data table.
• The specific data structure, columns, and row counts are unknown, limiting direct computational analysis.
• The data is based on a theoretical model; its applicability to real-world scenarios may require validation with empirical data.

Provenance

Source

figshare, authored by Qian Wang.

Collection Method

The data is derived from a theoretical game-theoretic model presented in the accompanying research paper.

Freshness

The associated record was last updated on 2026-03-20.