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<p>India’s vast digital commerce sector is being rapidly transformed by recommendation systems (RS) that shape the purchasing decisions of an exceptionally diverse consumer market comprising over 900&#xa0;million internet users, 22 scheduled languages, and a pronounced rural-urban digital divide. While scholarly attention to algorithmic accuracy, personalisation, and business performance has grown substantially, a systematic synthesis of responsible RS design in the Indian context remains absent. This paper presents a systematic literature review of 40 peer-reviewed articles published between 2020 and 2025, identifying eight key research gaps at the intersection of technical architecture, consumer welfare, regulatory compliance, and multi-stakeholder fairness within India’s specific context. Drawing on these gaps, we propose the Responsible Retail Recommendation System (R3S) framework—a unified design architecture that integrates six previously isolated streams: privacy-preserving computation, fairness-aware ranking, multilingual explainability mechanisms, compliance with the Digital Personal Data Protection Act (DPDPA) 2023 and related Indian legislation, consumer wellbeing monitoring, and sustainable consumption incentivisation. The framework is aligned with the DPDPA 2023, the Consumer Protection (E-Commerce) Rules 2020, the Information Technology Act 2000, and the NITI Aayog’s Responsible AI for All principles. We further articulate a longitudinal empirical research agenda tailored to India’s socio-economic and regulatory conditions. The paper makes three novel contributions: an India-specific gap taxonomy, an actionable multi-dimensional framework calibrated to Indian market conditions, and a research roadmap that reorients the RS discipline from optimising commercial engagement to optimising responsible personalisation in one of the world’s most consequential digital economies.</p>

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Towards a unified responsible recommendation system framework for Indian retail and digital marketing: bridging technical safeguards, consumer welfare, and regulatory compliance

  • 期刊论文

  • 发表日期：

    2026年5月11日

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  • Divyakant T. Meva,
  • Kalpesh Popat,
  • Himanshu Maniar,
  • Rahul J. Nikam,
  • Madhuri Parekh,
  • Ajay Patel

摘要

India’s vast digital commerce sector is being rapidly transformed by recommendation systems (RS) that shape the purchasing decisions of an exceptionally diverse consumer market comprising over 900 million internet users, 22 scheduled languages, and a pronounced rural-urban digital divide. While scholarly attention to algorithmic accuracy, personalisation, and business performance has grown substantially, a systematic synthesis of responsible RS design in the Indian context remains absent. This paper presents a systematic literature review of 40 peer-reviewed articles published between 2020 and 2025, identifying eight key research gaps at the intersection of technical architecture, consumer welfare, regulatory compliance, and multi-stakeholder fairness within India’s specific context. Drawing on these gaps, we propose the Responsible Retail Recommendation System (R3S) framework—a unified design architecture that integrates six previously isolated streams: privacy-preserving computation, fairness-aware ranking, multilingual explainability mechanisms, compliance with the Digital Personal Data Protection Act (DPDPA) 2023 and related Indian legislation, consumer wellbeing monitoring, and sustainable consumption incentivisation. The framework is aligned with the DPDPA 2023, the Consumer Protection (E-Commerce) Rules 2020, the Information Technology Act 2000, and the NITI Aayog’s Responsible AI for All principles. We further articulate a longitudinal empirical research agenda tailored to India’s socio-economic and regulatory conditions. The paper makes three novel contributions: an India-specific gap taxonomy, an actionable multi-dimensional framework calibrated to Indian market conditions, and a research roadmap that reorients the RS discipline from optimising commercial engagement to optimising responsible personalisation in one of the world’s most consequential digital economies.