  We consider linear-quadratic-Gaussian (LQG) network games in which agents
have quadratic payoffs that depend on their individual and neighbors' actions,
and an unknown payoff-relevant state. An information designer determines the
fidelity of information revealed to the agents about the payoff state to
maximize the social welfare. Prior results show that full information
disclosure is optimal under certain assumptions on the payoffs, i.e., it is
beneficial for the average individual. In this paper, we provide conditions
based on the strength of the dependence of payoffs on neighbors' actions, i.e.,
competition, under which a rational agent is expected to benefit, i.e., receive
higher payoffs, from full information disclosure. We find that all agents
benefit from information disclosure for the star network structure when the
game is symmetric and submodular or supermodular. We also identify that the
central agent benefits more than a peripheral agent from full information
disclosure unless the competition is strong and the number of peripheral agents
is small enough. Despite the fact that all agents expect to benefit from
information disclosure ex-ante, a central agent can be worse-off from
information disclosure in many realizations of the payoff state under strong
competition, indicating that a risk-averse central agent can prefer
uninformative signals ex-ante.
