The dark side of information systems use: Three essays

Abstract

Information systems (IS) have various benefits to individuals and society and have become highly intertwined with everyday life. Even though these technologies are very useful, it has also introduced unique sets of societal challenges. Personal use of IS can have “dark sides” including IT use related stress, interruptions, addiction, and misuse. We will focus on three major aspects of how information systems affect individuals in a negative way –problematic use of technology, privacy concerns, and the role of IS in shaping cognitive bias. This dissertation proposal consists of three essays that investigates these dark side of IS use. First essay examines technology overuse (or technology addiction) and how it affects an individual’s mental wellbeing. We propose and empirically test a feedback relationship between increased technology use and mental wellbeing using cognitive theories of psychology. This new model addresses the conflicts in the current literature. In second essay, we use communication privacy management theory and signaling theory to examine different ways to mitigate privacy concerns. Individuals use devices that follow them everywhere including wearables like fitness trackers or smart watches, smart phones, etc. that constantly collect data about them. The pervasiveness of these technology has made us vulnerable to privacy and security concerns. Our study suggests that privacy policies, governmental regulation, and privacy settings are information signals that can reduce user’s privacy concerns. In addition, internet and other information media are associated with increase in hate crimes. Social media can provide a huge amount of information that may influence the cognitive biases of individuals which can further affect their judgement and action. Hence, it is important to understand how information system, particularly social media, shape the cognitive biases in individuals. In the third essay, we examine how social media influence cognitive bias using dual process theory.