To target crowding at locations, decision support systems (DSS) increasingly feature crowding information (CI) to indicate how much of a location's available capacity is occupied. Yet, little is known about how and why the timeliness of such CI (e.g., “updated just now”) influences users' selections of differently crowded locations and the effectiveness of location recommendations. Addressing this knowledge gap is, however, important to understand how to design DSS interfaces that prevent (over)crowding and improve related DSS reuse intentions. Drawing on construal level theory, we applied a mixed-methods approach comprising a quantitative and a complementary qualitative study. First, we conducted an online experiment in which 171 participants selected between differently crowded bars. The quantitative data provides evidence that high (vs. low) timeliness of CI leads users to select less crowded bars and raises users' DSS reuse intentions. Yet, the effect of high (vs. low) timeliness of CI on location selection is unexpectedly cancelled out when location recommendations are displayed. In subsequent qualitative interviews with DSS users we find that even though high (vs. low) timeliness of CI affords more conscious elaboration on CI's costs and benefits and increased trusting beliefs, present (vs. absent) location recommendations decrease one's cognitive effort and are more influential than timeliness of CI with regard to the actual location selection. Furthermore, high (vs. low) timeliness of CI enhances positive user perceptions, explaining the increased DSS reuse intentions. Overall, we provide novel insights on the role of timeliness of information for DSS to influence crowding behavior.