Abstract
This dissertation examines the potential unintended consequences of unstructured data on management accountants’ judgment, decision-making, and actions. Based on the cognitive load theory and information overload concepts, I predict that the cognitive overload created by the presentation of unstructured data will increase the level of ethical blindness in management accountants’ decision-making processes. Using the environmental, technological, human, and organizational (ETHOs) framework and the moral awareness ethical decision-making model, I examine whether ambiguity tolerance and the perception of digital/analytical self-efficacy moderate the relation. An experiment was conducted with upper-level accounting students from three liberal arts universities. Participants were tasked with making an ethically consequential business decision based on one of two kinds of information: (1) information consisting only of traditional structured data or (2) information consisting of a variety of unstructured data with minimal traditional data. The findings demonstrate that decision-makers experience higher levels of ethical blindness when presented with unstructured data. The study does not find a moderation effect of digital/analytical self-efficacy or ambiguity tolerance on this relation. This study contributes to the existing literature on accounting information systems, management accounting, and ethics. The findings highlight the importance of integrating ethical concepts into accounting and data analytics curriculum/course development and professional training and provide practical insight to enhance management control systems related to the utilization of unstructured data in the decision-making process.