Distributed choice-based control systems are systems for which the applied control of each agent is individually selected according to the agent's choice. They form an interesting class of decentralized systems in which control strategies are entangled with the information structure. This paper focuses on an important subset of these systems that are governed by linear dynamics. We show how choice-based targets can be realized without explicit communication and how control actions can serve as signaling tools. In comparison with strategies using explicit communication methods, the value of information in facilitating cost reduction is revealed. Our solution approach makes use of a composite cost function that incorporates both control costs and target errors for benchmarking.