DIGITAL CARBON JUSTICE IN SPORT: ASSESSING TRANSBOUNDARY EMISSION SHIFTS AND SOCIAL BURDENS IN FOOTBALL AND ESPORTS

Title:Digital Carbon Justice in Sport: Uncovering Transboundary Emission Shifts and Social Burdens in Football and EsportsStudy Overview:This study develops and tests the concept of Digital Carbon Justice (DCJ), a new middle-range theory that explains how digital sport systems, such as streaming platforms, esports ecosystems, and smart stadiums, redistribute environmental burdens across time, place, and population. While digitalisation in sports is often framed as enabling sustainability, our findings reveal that efficiency gains are conditional, distributed, and frequently obscured by organisational communication practices. This study employs a multi-method design, randomised field experiments, staggered difference-in-differences, agent-based simulation, and computational text analysis to showcase three fundamental theoretical contributions.i. Rebound as governable: efficiency-induced rebound can be mitigated through eco-defaults and sustainability information systems.Infrastructural displacement: the siting of content delivery networks and data centres redistributes carbon and water burdens across geographies.Measurement justice: disclosure–performance gaps are structurally produced by accounting regimes and attenuated by independent assurance.Data Description:This data preserves the joint distributions, treatment effects, and diagnostic statistics reported in the appendices, while eliminating any risk of personal identification or contractual disclosure restrictions.i. Unit of analysis: viewer session (football and esports).Sample size: 300,000 sessions (scalable to 5.92 million, as reported in the study).Variables include:a. Device characteristics (desktop, mobile, TV, VR)Country ISO codes, grid carbon intensity (kgCO₂e/kWh), and water stress indicesExperimental treatments (eco-default assignment, real-time prompts, circularity defaults) and complianceFan behaviours (watch-time, bitrate choice, opt-up behaviour, low-energy adoption)Outcomes: energy per viewer-minute (Wh), emissions per session (gCO₂e, location-based)Organisational metadata (football vs esports, club/league identifiers)Supporting Materials:The repository includes full replication appendices:i. Appendix A: descriptive statistics, representative sample, correlation matrix, and collinearity diagnostics.Appendix B: regression results (intention-to-treat and 2SLS-style).Appendix C–E: robustness, text analysis codebook, and validation outputs.The README file provides a description of the generation code, seed values, and scaling instructions.Use and Limitations:The dataset is suitable for reproducing all descriptive and inferential analyses reported in the article. It can be used by scholars interested in digital sustainability, rebound effects, infrastructural justice, and greenwashing in the sport sector.