A Web‑Based Multiplayer Common‑Pool Resource Game Platform

Vasileios Tzimourtos ORCID

    Received: 15 May 2025; Revised: 6 July 2025; Accepted: 8 July 2025; Published: 22 July 2025

    Abstract

    The paper introduces a web‑based platform for conducting multiplayer common‑pool resource (CPR) games, replicating the experimental framework of Ahn et al. Built using technologies such as PHP, MySQL, HTML5, and JavaScript the platform facilitates remote and synchronous gameplay in structured groups with configurable settings. Players extract tokens from a shared resource over multiple rounds, with payoffs determined by token‑order pricing and optional costly punishment stages. The system supports dynamic group formation, randomized player order, and round‑based synchronization to ensure fairness. It includes real‑time coordination via AJAX polling; a responsive Bootstrap interface; administrative controls, and live monitoring through Grafana dashboards. Data integrity is maintained using server‑side validation, prepared S.Q.L. statements, and transactional database updates, with all actions logged in a normalized relational schema. The platform addresses technical challenges such as session timeouts, synchronization delays, and dropouts using heartbeat callbacks, waiting screens, and robust state checks. Designed for extensibility, it can support different game‑theoretic designs and is suitable for both lab and remote experiments. Future enhancements include WebSocket‑based real‑time communication and Docker‑based deployment for reproducibility. By offering a customizable, secure, and scalable CPR experiment environment with real‑time feedback and comprehensive logging, this platform serves as a valuable tool for advancing research in experimental economics, particularly in cooperation, punishment mechanism, and resource governance. The platform demonstrates reliable performance with low‑latency synchronization and minimal dropout‑related issues. Compared to tools like oTree and LIONESS Lab, it offers a more lightweight and modular alternative optimized for small‑scale deployment, remote teaching, and rapid experimental design.

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