Abstract—Evaluating potential host cities for major sporting events increasingly requires rigorous consideration of environmental responsibility due to global environmental degradation. Existing site selection models often rely on limited qualitative indicators, focusing heavily on economic development and logistics, which fail to capture the complex environmental impacts of large-scale events. To bridge this gap, this study proposes a comprehensive multi-criteria environmental sustainability evaluation framework, using the NFL Super Bowl host city selection as a case study. Six core quantitative indicators are developed to represent environmental performance: Water Resource Index, Waste Circularity, Transit Carbon Control, Thermal Adaptability, Energy Efficiency and Cleanliness, and Ecological Quality. To integrate subjective expert knowledge with objective data variation, a Hybrid Weighting Method fusing the Analytic Hierarchy Process (AHP) and the Entropy Weight Method is employed, followed by the TOPSIS method for comprehensive ranking. Application of this framework to nine U.S. candidate cities reveals that Seattle, Washington, exhibits the optimal environmental sustainability profile, driven by its robust clean energy infrastructure and efficient waste circularity. Furthermore, sensitivity analysis demonstrates the high stability and robustness of the model under weight perturbations. This framework provides policymakers and sports organizations with a quantitative, scalable tool for prioritizing ecological integrity in mega-event planning.
Keywords—site selection, environmental sustainability, multi-criteria decision making, TOPSIS, hybrid weighting
Cite: Yi Lu, Xinlei Shen, and Xiangjun Zhang, "Optimizing Host City Selection for Mega-Sporting Events: An Environmental Sustainability Perspective," International Journal of Engineering and Technology, vol. 18, no. 3, pp. 106-110, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (
CC BY 4.0).
