This study aimed to evaluate the potential of the Qatar 2022 World Cup in promoting bonding, bridging, and linking social capital within the host community and beyond. A total of 403 respondents completed a researcher-made questionnaire 12 months after the event. One sample t-test indicated that all three forms of social capital exceeded the test value significantly (P < 0.01). Residents of Qatar scored significantly higher in bridging and linking social capital compared to participants from other countries (P < 0.01). Arab respondents exhibited greater levels of linking social capital compared to non-Arab Muslims, whereas non-Arab Muslims demonstrated higher levels than respondents from other nationalities (4.444 > 3.852 > 3.349, P < 0.01). Residing in the host community and reaping benefits from an event can lead to a more positive perception of the event's social capital. Facilitating the participation of individuals with diverse backgrounds in sporting events can help to develop social capital across borders.

Urban managers and decision-makers may approach Urban Environmental Quality (UEQ) assessment with perspectives that range from highly pessimistic to highly optimistic scenarios. The objective of this study was to introduce a scenario-driven spatial decision support system framework for optimizing UEQ zoning. The proposed framework includes six steps: (1) building a geodatabase of criteria, (2) standardizing criteria using minimum and maximum methods, (3) determining criteria weights using the Analytic Hierarchy Process (AHP) method, (4) combining criteria and creating scenarios using the OWA method, (5) analyzing UEQ maps with statistical analyses, and (6) examining variability through histogram analysis of UEQ values across scenarios. The results indicate that, among environmental and infrastructural criteria, air pollution and population density had the most significant impact on UEQ zoning in Isfahan city. In the five decision-making scenarios (highly pessimistic, pessimistic, neutral, optimistic, and highly optimistic), 8% (19), 12% (15), 16% (12), 21% (8), and 25% (5) of Isfahan’s area were classified as poor, respectively. Additionally, the percentage of the population in poor classes across the scenarios was 5% (14), 10% (11), 13% (7), 17% (5), and 20% (3), respectively. The findings demonstrate that the proposed framework offers high flexibility and capability for assessing UEQ across different decision-making scenarios.