Aug 2026· Journal of Macromarketing· 0 citations· 56 references
TL;DR
Results show that structuring ethical recommendations through a plural AI architecture enhances consumers’ self–brand connection and strengthens self-brand connection and purchase intentions, suggesting plurality can function as an equity-enhancing design feature.
Abstract
Artificial intelligence (AI) increasingly structures how consumers encounter, evaluate, and select marketplace options, raising fundamental questions about autonomy, empowerment, and welfare-enhancing choice environments. While prior work has focused on what algorithms recommend, less is known about how recommendation system architecture shapes the experience of choice. Across three experiments, this research examines the societal and psychological implications of perceived algorithmic plurality, defined as consumers’ perception that recommendation authority is distributed across multiple distinct AI agents, each guided by distinct evaluative criteria. Results show that structuring ethical recommendations through a plural AI architecture enhances consumers’ self–brand connection. Study 2 demonstrates that plural recommendations increase perceived autonomy, which strengthens self–brand connection and purchase intentions. Study 3 shows these effects are strongest among low-knowledge consumers, suggesting plurality can function as an equity-enhancing design feature. By shifting attention from algorithmic outputs to the socio-technical structure of AI nudges, this research advances understanding of consumer emancipation in digital marketplaces.
Conditions under which AI design choices can attenuate stereotype‐congruent preferences are identified and evidence regarding the psychological processes associated with these shifts is provided, offering actionable insights for managers and policymakers seeking to design AI agents that support more equitable human–AI...
Marius C. Claudy, Anshu Suri, Sheng-Nan Ren et al.· Psychology & Marketing· 0 citations
It is concluded that decision autonomy under AI personalisation is best understood not as binary but as a matter of degree, shaped by platform design choices, consumer digital literacy, and the regulatory environment in which the platform operates.
This article synthesizes recent empirical evidence to demonstrate that personalization can significantly enhance sustainable consumption when implemented through transparent, reasoning-enabled AI systems that prioritize ethical data stewardship.
Raghava B S, D. K S· International Scientific Jou...· 0 citations
It is argued that explainable AI (XAI) constitutes a necessary, and currently undertheorised, layer in the design of consumer-facing AI systems, and a theoretical foundation for researchers, practitioners and policymakers to close the gap between AI capability and accountability in marketing.
Sakshi Bhati, Nikita Singh· Asia-Pacific Journal of Mana...· 0 citations
Results indicate that AI-driven personalization, brand experience, perceived value, and social proof significantly enhance algorithmic fairness perception, and AI-driven personalization, brand experience, perceived value, and algorithmic fairness perception substantially increase purchase intention, while social proof...
Roby Nur Akbar, Kamaluddin, Nirwana et al.· Indonesian Journal Economic...· 0 citations
This study investigates whether autonomy deprivation resulting from overchoice environments predicts individuals' attraction to morally decisive fictional antagonists and unconventional brand personalities. Drawing on Self-Determination Theory, the Paradox of Choice, media psychology, and consumer behaviour literature,...
Chirag Jain· International journal of res...· 0 citations
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