From Ethical Consumption to Algorithmic Finance: A Comparative Qualitative Study of Human Judgment, AI Decision Support, and Sustainable Financial Behavior among Students

Abstract

The rapid expansion of digital marketplaces has transformed not only how students shop but also how they express values, identities, and moral orientations through consumption. While existing research predominantly conceptualizes ethical consumption as a rational, intention-driven behavior, it often overlooks the emotional, social, and identity-based processes underlying everyday purchase decisions—especially in platform-mediated environments. This qualitative study adopts a grounded theory approach to explore how university students construct meaning around ethical digital consumption in e-commerce contexts.

Data were collected through semi-structured interviews with 30 undergraduate students aged 18–23, selected using purposive and snowball sampling. Using open, axial, and selective coding procedures, the analysis revealed that ethical consumption among students is not a stable behavioral pattern but an evolving identity process shaped by emotional conflict, social validation, peer and influencer narratives, and platform trust.

Six dominant emotional orientations—guilt, pride, confusion, anger, indifference, and happiness—emerged as central to how students evaluated their purchases and moral self-concept. Based on these findings, the study proposes the Ethical Consumption Identity Formation Model, which explains how awareness, emotional appraisal, social interpretation, and trust interact to shape value-based digital consumption.

This study contributes to sustainability and consumer research by theorizing ethical consumption as a lived, identity-driven process rather than a purely rational choice. Practically, it offers insights for educators, e-commerce platforms, and policymakers seeking to design inclusive, transparent, and emotionally resonant sustainability interventions for young consumers.

To extend the grounded theory findings, this study incorporates a second qualitative dataset collected through short telephonic interviews (N = 27) examining AI-assisted financial decision-making among students. Comparative analysis indicates that while AI improves efficiency, fraud prevention, and financial awareness, participants continue to rely heavily on human judgment due to concerns regarding transparency, emotional disconnect, and accountability. Ethical discomfort, frequent human override behavior, and fragmented responsibility attribution emerged as central patterns. Together, the findings demonstrate that sustainable digital financial behavior is shaped not by automation alone but through hybrid human–AI decision processes, where emotional appraisal and trust act as key mediating mechanisms. This comparative perspective expands the Ethical Consumption Identity Formation Model by showing that similar identity-based negotiations govern both consumption and AI-mediated financial decisions.