Maladaptive Consumption: Identifying Novel Roots and Remedies for Undesirable Consumer Outcomes

Abstract

How can we improve the lives of consumers? Recent initiatives like the “Better Marketing for a Better World” and “Transformative Consumer Research” movements have posed this question. This comes as no surprise as the pandemic, inflation, and other recent events have uncovered a number of issues that consumers are facing. From some individuals not investing enough for their retirement but gambling away money in sports betting to others struggling with mental health issues but refusing to get help from medical staff or people in their social surroundings. What are some factors that these consumers have in common, and how can the marketing discipline help promote their well-being? In three essays, this dissertation aims to provide answers to these questions by identifying two novel causes of maladaptive consumer outcomes and a promising intervention to prevent them. The first essay examines gamified financial platforms (e.g., investment apps equipped with leaderboards, levels, or other game elements) and how they can cause consumers to make poor financial decisions, treating investing more like gambling and thereby jeopardizing their financial well-being. The second essay investigates the rising phenomenon of entertainment betting, showing that wagering money on sports games, television shows, and other events in the hope of a quick thrill can actually backfire as illustrated by a diminished enjoyment among fans. Finally, the third essay shifts the level of analysis from potential causes of maladaptive consumer outcomes to a promising intervention, demonstrating that relationships with pets are capable of mitigating psychological pain to a greater extent than most interpersonal relationships, an effect that can be explained by consumers’ perceptions of unconditional love. Across the three essays, this dissertation employs a range of different methodologies from in-depth interviews and large-scale surveys to experimental methods and secondary data analyses.