{
  "id": 3037,
  "url": "https://arxiv.org/abs/2607.09956v1",
  "title": "Optimizing ARDL Models for Retail Sales Forecasting and Fair Pricing",
  "summary": "Pricing food products to balance profitability with consumer welfare is a central challenge for retailers. Dynamic pricing is widely used to maximize revenue, yet most pricing models optimize business objectives while overlooking consumer fairness. This paper studies the risk of consumer exploitation under dynamic food pricing in Canada and proposes a methodology that embeds fairness constraints directly into retail sales forecasting. We model total retail trade sales with a log--log Autoregress",
  "authors": "Sujay Uday Rittikar",
  "category": "research",
  "topics": "bias-fairness",
  "orgs": null,
  "regions": "canada",
  "published_at": "2026-07-10T20:19:38.000Z",
  "fetched_at": "2026-07-14T16:11:46.979Z",
  "source_slug": "x-arxiv-fairness-query",
  "source_name": "arXiv fairness query",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3037",
  "original_url": "https://arxiv.org/abs/2607.09956v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}