Despite the growing body of research in related disciplines, including economics, management, politics, psychology, and sociology, marketing research has largely overlooked the downstream consequences of economic inequality, despite its undeniable impact on individuals' consumption decisions and experiences. This dissertation endeavors to bridge this knowledge gap by uncovering two novel consumer consequences of economic inequality. To accomplish this, it draws upon a diverse range of data sources, including individual-level experimental and survey data, as well as aggregate-level transaction and census data. Additionally, it examines economic inequality across multiple levels, encompassing communities, counties, states, and countries, and operationalizes it both as objective and perceived economic inequality. In Essay 1, I investigate how economic inequality in a consumer's region affects their access to peer-to-peer (P2P) services. Across diverse types of P2P services, I find convergent evidence that increased economic inequality in a consumer's region reduces providers' willingness to serve them, ultimately resulting in their diminished access to P2P services. This adverse effect of economic inequality can be attributed to providers perceiving consumers from more unequal regions as less trustworthy. This perception leads them to perceive heightened financial risks associated with serving these consumers. Moreover, this negative impact of economic inequality attenuates when providers perceive greater interpersonal similarity with consumers from unequal regions. In Essay 2, I explore how economic inequality within one's society affects their education decisions through the lens of perceived education premium. Firstly, it encourages people to attend college as it amplifies the perceived education premium of college—the income gap between college graduates and high school graduates. Secondly, it motivates people to choose majors with higher earning potential but lower personal interests, as opposed to those that align more with their genuine interests but pay less. This shift towards prioritizing extrinsic motivations over intrinsic ones is driven by people's perception of a more significant education premium between majors—the income disparity between higher-paying and lower-paying majors. / Doctor of Philosophy / Economic inequality, defined as the unequal distribution of income among various groups in a society, has been on the rise globally in recent decades. Amid the growing economic inequality, researchers have been delving into its profound impacts on individuals across diverse domains, exploring its influences on their mindsets, perspectives on the world, social lives, and overall well-being. It's surprising that there has been relatively little research on how economic inequality affects people's consumption decisions and experiences, given its undeniable influence on them. In this dissertation, I explore the impacts of economic inequality on consumers' access to P2P services and education decision-making. In Essay 1, I investigate how economic inequality in a consumer's region affects their access to peer-to-peer (P2P) services. I examine whether P2P providers are equally willing to serve consumers from regions with varying levels of economic inequality. I reveal a disconcerting reality: providers are less willing to offer P2P services to consumers from more unequal regions, driven by the perception of these consumers as less trustworthy and posing a higher financial risk. These differing attitudes ultimately lead to reduced access to P2P services and region-based discrimination for consumers from regions characterized by higher economic inequality. Fortunately, these adverse outcomes can be mitigated by an increase in perceived interpersonal similarity between providers and consumers. In Essay 2, I investigate how economic inequality in one's society shapes their education decisions. I find that as economic inequality rises, people become more willing to pursue a college education because they perceive a wider income gap between well-educated individuals and those with lower levels of education. Besides college decisions, economic inequality also influences people's choice of major for a similar reason. In a society characterized by greater economic inequality, people gravitate towards majors that promise higher earning potential, even if these fields do not align closely with their personal interests. This preference is driven by their perception of a greater wage difference between higher- and lower-paying majors. These findings provide policy implications for several pressing challenges in higher education.

The topic of this thesis is AI recruitment chatbots, digital discrimination, and data feminism (D´Ignazio and F.Klein 2020), where I aim to critically analyze issues of bias in these types of human-machine interaction technologies. Coming from a professional background of theatre, performance art, and drama, I am curious to analyze how using AI and social robots as hiring tools entails a new type of “stage” (actor’s space), with a special emphasis on social acting. Humans are now required to adjust their performance and facial expressions in the search for, and approval of, a new job. I will use my “theatrical glasses” with an intersectional lens, and through a methodology of cultural analysis, reflect on various examples of conversational AI used in recruitment processes. The silver bullet syndrome is a term that points to a tendency to believe in a miraculous new technological tool that will “magically” solve human-related problems in a company or an organization. The captivating marketing message of the Swedish recruitment conversational AI tool – Tengai Unbiased – is the promise of a scientifically proven objective hiring tool, to solve the diversity problem for company management. But is it really free from bias? According to Karen Barad, agency is not an attribute, but the ongoing reconfiguration of the world influenced by what she terms intra-actions, a mutual constitution of entanglement between human and non-human agencies (2003:818). However, tech developers often disregard their entanglement of human-to-machine interferences which unfortunately generates unconscious bias. The thesis raises ethical questions of how algorithmic measurement of social competence risks holding unconscious biases, benefiting those already privileged or those acting within a normative spectrum.