Buy Now, Pay Later (BNPL) in a VUCA Economy: A Conceptual Exploration
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Abstract
The rapid expansion of Buy Now, Pay Later (BNPL) services has significantly reshaped contemporary consumer credit ecosystems, particularly within the context of a VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) economy. Despite its growing adoption, existing literature remains fragmented, with limited integration of macro-environmental uncertainty, platform design mechanisms, and consumer behavioral dynamics. Addressing this gap, the present study adopts a theory-building conceptual approach to develop a multi-level framework that examines BNPL as a fintech-driven consumption model operating at the intersection of environmental uncertainty, technological affordances, and behavioral finance. Drawing upon Prospect Theory, Mental Accounting Theory, the Technology Acceptance Model (TAM), and the Theory of Planned Behavior (TPB), the study conceptualizes how BNPL platforms leverage perceived affordability, reduced cognitive friction, and persuasive digital design to influence consumer decision-making. The proposed framework integrates VUCA conditions as a macro-level driver, platform characteristics as meso-level enablers, and behavioral outcomes such as impulsive consumption and financial stress as micro-level consequences, while also incorporating moderating roles of financial literacy and regulatory oversight. The findings highlight the paradoxical nature of BNPL, positioning it simultaneously as a facilitator of financial inclusion and a potential driver of consumer over-indebtedness in uncertain economic environments. By offering a structured and integrative conceptual model, this study contributes to the emerging discourse on digital credit systems and extends fintech literature by embedding BNPL within a VUCA-driven behavioral framework. The paper concludes with implications for policymakers, financial institutions, and digital platform designers, emphasizing the need for responsible innovation, ethical interface design, and adaptive regulatory mechanisms.