Sustainable Preference Externalities Research

Modeling willingness-to-pay shifts under social information on digital platforms, aligning with sustainability and user welfare.

      Research Question

      How do peer behaviors, social signals, and algorithmic curation influence individual preference formation, willingness-to-pay (WTP), and the diffusion of sustainable consumption norms in digital marketplaces?

Background & Motivation

Digital platforms create complex ecosystems where user preferences are shaped by social influence and algorithmic signals rather than isolated choices. These dynamics generate preference externalities that shift willingness-to-pay systematically.

Understanding these mechanisms is crucial for:

Platform design & optimization: Encouraging fair and sustainable recommendation strategies
Sustainable pricing models: Embedding ESG and green incentives into consumption choices
Regulatory & policy development: Informing transparency and consumer protection in digital markets
User welfare maximization: Balancing personalization with long-term sustainable outcomes

Methodology

🔬 Causal Inference Framework

A unified identification strategy that combines:

Instrumental variables (IV) for isolating peer influence
Difference-in-differences (DiD) for platform/policy shocks
Causal machine learning (e.g., causal forests, heterogeneous treatment effects) for uncovering subgroup dynamics

📊 Data Sources

Anonymized e-commerce transactions
Social media engagement and algorithmic recommendation signals
Cross-platform digital consumption behaviors
Pilot datasets on green product adoption and sustainable purchasing

Key Findings

🎯 Peer Influence Effects

Peer behavior shifts WTP by 15–25%, with stronger amplification in sustainable consumption categories.

⚡ Algorithmic Signal Amplification

Recommendation systems amplify externalities by 30–40%, creating feedback loops that can accelerate or dampen green adoption.

🌍 Heterogeneous Impacts

Effects differ by user demographics, product type, and platform context. Importantly, sustainable product categories show higher sensitivity to norm framing and identity signals.

Policy & Sustainability Implications

Platform Governance: Build transparent and accountable recommendation systems aligned with sustainability goals
Consumer Protection: Develop safeguards against manipulation of preference externalities
Sustainability Transitions: Inform policies that leverage digital platforms as catalysts for ESG adoption and green diffusion
Competition Policy: Address network effects and ensure fair access to sustainable product visibility

Next Steps

Develop counterfactual simulations for sustainable preference shifts
Build predictive models for WTP evolution in green consumption
Design platform interventions (e.g., identity cues, incentives) to foster sustainable adoption
Expand research to urban air mobility (UAM) and other emerging sustainability-related markets

      Impact

      This research supports sustainable platform governance by combining causal inference with behavioral modeling. Presented at INFORMS 2025, with applications in policy design and platform ESG strategies.