Influencer marketing practice predominantly favors same-niche partnerships; however, industry evidence suggests that unconventional pairings can sometimes outperform traditional matches, highlighting a knowledge gap regarding how collaboration structure influences consumer response. Drawing on Optimal Distinctiveness Theory, this research examines whether cross-niche collaborations enhance brand evaluations by fulfilling concurrent desires for inclusion and differentiation. Four controlled experiments (total N = 1482) employing Instagram-style stimuli and behavioral intention measures compare same- versus cross-niche alliances while manipulating or measuring consumers’ need for uniqueness and category expertise. Across studies, cross-niche (versus same-niche) collaborations consistently improve brand attitude, an effect fully mediated by heightened perceptions of brand innovation. Moderation analyses reveal that this indirect effect is amplified among consumers high in need for uniqueness but attenuated—and in some cases reversed—among category experts, who tend to prefer the depth signaled by same-niche partnerships. Alternative explanations, including curiosity, source credibility, and message liking, are empirically ruled out. These findings extend Optimal Distinctiveness Theory to influencer branding by identifying collaboration type as a market-level cue signaling innovation while refining influencer effectiveness models through a dual-contingency framework that incorporates motivational and knowledge-based audience factors. From a managerial perspective, the results suggest deploying cross-niche alliances when targeting novelty-seeking or novice segments while preserving niche purity or offering technical justification when addressing expert consumers, thereby aligning collaboration strategies with audience composition.

The persistent challenge of designing digital interfaces that minimize users’ perceived waiting time remains critical for user satisfaction and conversion rates. This research integrates Attentional Gate Theory to investigate how loading animation type (static vs. dynamic) influences perceived waiting duration through temporal attention focus, and examines moderating roles of task involvement and browsing goal orientation. Across four online experiments—Study 1 (N = 198, MTurk) tested the main effect of animation type; Study 2 (N = 411, Prolific) validated full mediation via temporal attention focus using PROCESS analysis; Study 3 (2 × 2 design, N = 400, Prolific) examined task involvement as a moderator; and Study 4 (2 × 2 design, N = 400, Prolific) explored hedonic versus utilitarian browsing goals—the dynamic animation consistently shortened perceived waiting time relative to static displays. Mediation analyses confirmed that reduced temporal attention focus fully explains this effect, which is amplified under low task involvement and hedonic browsing but attenuated when involvement is high or goals are utilitarian. Theoretically, this work extends Attentional Gate Theory to user experience design by uncovering cognitive processes underlying time perception during waits. Managerially, it offers evidence-based recommendations for tailoring loading animations to user context, ultimately enhancing satisfaction and reducing abandonment.