Abstract Contemporary consumers increasingly function as human–machine hybrids, challenging traditional consumer behavior models that assume a single, bounded human decision-maker. This conceptual paper introduces the Social Cyborg Consumer framework, which integrates posthumanist philosophy of technology with mainstream consumer behavior research and behavioral economics to reconceptualize consumer choice as co-produced by human cognition and machine intelligence. Building on classical decision models and digital consumer behavior research, we argue that extant theories often treat AI, algorithms, and platforms as external influences rather than as constituents of the consumer’s own decision system. We develop six socio-technical “cyborg dimensions” of consumer behavior—Extended Cognition, Hybrid Agency, Algorithmic Choice Architecture, Networked Self, Data-Driven Personalization, and Attention Governance—each grounded in posthumanist and socio-technical theory (e.g., Haraway, Simondon, Stiegler, Latour, affordance theory) and behavioral concepts (bounded rationality, nudging, social influence, attention limits). Methodologically, we adopt a conceptual research design following MacInnis (2011) and Jaakkola (2020): an interdisciplinary literature review, abductive clustering of recurring themes, iterative refinement into six analytically distinct dimensions, and illustrative mini-cases from sectors such as e-commerce, digital platforms, financial services, and health. We present an integrated conceptual model that locates the dimensions across three layers (cognitive/agency core, social–data layer, and environmental/attention layer) and relates them to consumer autonomy and market ethics. The paper concludes by outlining sector-specific implications for retailers, platforms, financial and health service providers, and regulators, and by specifying avenues for empirical research that can test and extend the Social Cyborg Consumer framework.
Edu William (Fri,) studied this question.