The behavioral and signaling patterns observed in social animal groups, such as honeybee swarms or fish shoals, have inspired the research into collective decision-making, aiming to understand the pathways by which these groups reach consensus in a decentralized manner. Particularly, we examine how honeybees balance individual exploration and social information exchange to guide the swarm’s decision towards the best value alternative. Drawing from empirical findings we develop theoretical opinion contagion models that capture asocial behavior, non-linear interactions and inhibitory signalling, informing on how they affect the group’s ability to balance the decision’s speed, value or cohesion. Beyond the understanding of biological collective, our work also informs on the design of decentralized protocols for decision making for applications in robotics and artificial swarms.