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AI-powered personalization in e-commerce: Governance, consumer behavior, and exploratory insights from big data analytics

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  • Turki, Hager

Abstract

AI-powered personalization is revolutionizing digital commercial platforms, presenting a plethora of opportunities and challenges related to governance, ethical considerations, and consumer behavior. This research explores the effects of algorithmic personalization on consumer behavior by employing a log-log regression analysis on transaction-level datasets obtained from Amazon during the period spanning 2018 to 2022. By examining the elasticity of consumer spending in response to price and quantity changes, it is shown that both variables exhibit nearly unitary responses, indicating that spending patterns in AI-personalized environments follow strong and consistent elasticity trends. While direct exposure to personalization signals is not measured, the behavioral patterns observed are consistent with personalization effects typical of platforms like Amazon. The present investigation, which applies a reduced-form elasticity model, situates the interconnection between personalization systems and the broader societal context. The findings provide compelling evidence that adaptive personalization technologies are associated with shifts in consumer expenditure behaviors but also user autonomy and the dynamics of digital trust. The model identifies behavioral regularities that support interpretive insights into AI-mediated commerce. Analyzing from a governance perspective, the findings reveal notable deficiencies in both transparency and regulatory frameworks, particularly regarding the fairness and ethical management of personal data. With algorithmic personalization growing more inscrutable, this paper advocates for an interdisciplinary methodology that synthesizes behavioral insights with accountable technology governance. Ultimately, this study contributes to the ongoing discussions concerning the influence of AI on market dynamics and the promotion of socially responsible innovation within the digital economy.

Suggested Citation

  • Turki, Hager, 2025. "AI-powered personalization in e-commerce: Governance, consumer behavior, and exploratory insights from big data analytics," Technology in Society, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:teinso:v:83:y:2025:i:c:s0160791x25002234
    DOI: 10.1016/j.techsoc.2025.103033
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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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