The Causes and Effects of Consumer Competence Perceptions

Consumers are constantly making consumption decisions and engaging in marketplace activities that require some level of competence. In other words, consumers possess and require some knowledge, skills, and abilities to engage in the marketplace and obtain what they want. But what causes consumers to infer they are or are not competent? And, what are the consequences of these competence inferences on consumer behaviour? This dissertation examines the role consumption plays in consumers’ inferences of their own competence to enhance our understanding of these issues. By integrating the literature on competence and attributions of blame, this dissertation develops a theory for when and how consumption influences self-perceptions of competence and how these self-perceptions of competence impact future consumer behaviours. Evidence from five studies suggests that consumers infer their own competence from their consumption outcomes, despite who is actually responsible for causing these outcomes. This means consumers potentially see themselves as incompetent for negative outcomes that are entirely firm-caused. This dissertation argues that people infer their own competence from firm-caused outcomes because they conflate their decisions made prior to an outcome with the cause of that outcome. This dissertation also examines how these variations in self-perceptions of competence can influence future consumer behaviours.

Governing Big Data: The Political Economy of Power, Knowledge and Consumer Finance in the Digital Age

This dissertation offers a critical international political economy (IPE) analysis of the ways in which consumer information has been governed throughout the formal history of consumer finance (1840 – present). Drawing primarily on the United States, this project problematizes the notion of consumer financial big data as a ‘new era’ by tracing its roots historically from late nineteenth century through to the present. Using a qualitative case study approach, this project applies a unique theoretical framework to three instances of governance in consumer credit big data. Throughout, the historically specific means used to govern consumer credit data are rooted in dominant ideas, institutions and material factors.