In this dissertation, I theorize on how gaslighting manifests in managerial and organizational settings. I discuss the process of gaslighting and how the use of various manipulation tactics manifests between people in organizations over time. I take three distinctive approaches to study this complex phenomenon. First, using a rich case study, I develop new theory to explain how one notorious child molester was able to sustain a career for decades while assaulting hundreds of children and young women. In doing so, I introduce the concept of gaslighting which previously has only been rigorously applied to intimate interpersonal relationships in domestic (e.g., at home) settings. In essay 2, I expand on the individual level theory developed in essay 1 to develop a more generalized theory of gaslighting in organizations. I situate gaslighting within a nomological net of related constructs and illustrate how gaslighting is a unique construct with different antecedents and consequences that occurs in organizations more often than it should. In my final essay, I build on one of the propositions developed in essay 2 and empirically test what antecedents are likely to influence whether or not a firm is accused of gaslighting on Twitter. Through doing so, I find …

AI-enabled information systems (AI-enabled IS) offer enhanced utility and efficiency due to their knowledge-based endowments, enabling human agents to assign and receive tasks from AI-enabled IS. As a result, this leads to improved decision-making, ability to manage laborious jobs, and a decrease in human errors. Despite the performance-based endowments and efficiencies, there are significant ethical concerns regarding the use of and delegation to AI-enabled IS, which have been extensively addressed in the literature on the dark side of artificial intelligence (AI). Notable concerns include bias and discrimination, fairness, transparency, privacy, accountability, and autonomy. However, the Information Systems (IS) literature does not have a delegation framework that incorporates ethics in the delegation mechanism. This work seeks to integrate a mixed deontological-teleological ethical system into the delegation mechanism to (and from) AI-enabled IS. To that end, I present a testable model to ethically appraise various AI-enabled IS as well as ethically evaluate delegation to (and from) AI-enabled IS in various settings and situations.

Supply chain transparency is principally focused on a company's efforts toward disclosing information about their products, and their supply chain operations to the public. Essay 1 is a conceptual paper that examines the risks of disclosing supply chain mapping information to consumers and proposes an approach to developing risk mitigation strategies. This essay also develops a set of supply chain mapping conventions that support the development of an agility-focused supply chain map. Essay 2 employs an experimental design methodology to examine the impact of disclosing the ethnicity of a supplier on consumers' behaviors, while also capturing the extent to which a consumers' ethnic identity and prosocial disposition influence their behaviors. Finally, also using an experimental design, Essay 3 analyzes consumer outcomes based on disclosing no, partial, and full supply chain transparency information, and accounts for heterogenous consumer traits such as the importance of information to a consumer and their perceived quality of information. Collectively, these essays advance the body of knowledge that seeks to understand the risks and benefits of supply chain transparency, by conceptually identifying risks and proposing an approach to minimize the risks associated with supply chain transparency, and by illuminating the conditions that prompt favorable consumer outcomes.