Our Fates Entwined: A Social and Psychological Perspective of Control in Corporate Governance

In this dissertation I examine how the exercise of board control at one firm can influence governance at other firms by affecting the social cognitions of other corporate leaders about their own board. Existing corporate governance research has focused on the dyad-level relationship between management and the board or other constituencies of the same firm and has raised a variety of questions about the efficacy of boards as a control mechanism. I develop a novel theoretical framework in which the actions of a single board, such as the dismissal of a CEO, can reverberate across multiple firms and affect the behavior of other CEOs that are likely to be aware of the dismissal. The theory developed in the first study suggests that a CEO is likely to experience sanctions against a fellow CEO in a way which generates deterrence by increasing the salience of the board’s power over management and describes contingencies under which such CEOs are likely to preemptively alter their behavior in order to avoid similar sanctions. This perspective uncovers a much broader effect of boards than has been identified in prior research by considering how a single act of control by a board at one firm can bolster control at multiple other firms, while incurring costs only at the originating firm. Whereas existing governance literature emphasizes reactive forms of control, such as dismissing a CEO at a firm that is already in decline, the theoretical perspective introduced here suggests a proactive form of control in which CEOs react to control at other firms by engaging in behaviors aimed at preempting a similar fate. In the second study, I extend this theoretical framework by considering how subjective feelings of common fate among CEOs can cause sanctions aimed at one CEO to have unintended consequences for strategic preferences due to intergroup biases that are activated by relatively automatic cognitive processes of self-categorization. Overall this dissertation develops a cross-level perspective on governance that suggests how micro level socio-cognitive sources of control can affect corporate governance across industry boundaries, at the field level.PHDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144114/1/gshani_1.pd

Dyadic Reinforcement Learning

Mobile health aims to enhance health outcomes by delivering interventions to individuals as they go about their daily life. The involvement of care partners and social support networks often proves crucial in helping individuals managing burdensome medical conditions. This presents opportunities in mobile health to design interventions that target the dyadic relationship -- the relationship between a target person and their care partner -- with the aim of enhancing social support. In this paper, we develop dyadic RL, an online reinforcement learning algorithm designed to personalize intervention delivery based on contextual factors and past responses of a target person and their care partner. Here, multiple sets of interventions impact the dyad across multiple time intervals. The developed dyadic RL is Bayesian and hierarchical. We formally introduce the problem setup, develop dyadic RL and establish a regret bound. We demonstrate dyadic RL's empirical performance through simulation studies on both toy scenarios and on a realistic test bed constructed from data collected in a mobile health study