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DESCRIPTION:\n\nFares Belkhiria\, a doctoral student at 91şÚÁĎÍř i
 n the area of Marketing will be presenting his research proposal entitled:
 \n\nThree Essays On Precision Retailing Across Scales: Habits\, Consumer R
 ecommendation Systems and Synthetic-Population Simulation\n\nFriday\, Janu
 ary 30\, 2026\, at 8:00am\n\nStudent Committee Chair: Professor Laurette D
 ubé\n\nPlease note that the presentation will be conducted in person.\n\n
 \nABSTRACT\n\nFood retail functions as a central choice infrastructure in 
 daily life\, shaping health\, affordability\, and wellbeing under conditio
 ns of bounded rationality\, limited time\, and marketing complexity. Despi
 te this significance\, health-oriented retail interventions often yield mo
 dest behavioral change. This dissertation examines why such interventions 
 underperform and proposes a framework for precision retailing\, integratin
 g behavioral science\, artificial intelligence (AI)\, and ecosystem modeli
 ng to design more effective and equitable strategies. The research adopts 
 the precision retailing paradigm\, which views food-system transformation 
 as requiring cross-disciplinary\, data-integrated\, and socially responsib
 le innovation. The first essay investigates how multiscale shopping habits
 —repetitive\, cue-conditioned patterns of choice across items\, categories
 \, and stores—shape responsiveness to price promotions and health nudges. 
 Using multi-year loyalty data and machine-learning–based habit measures\, 
 the study demonstrates that habits systematically moderate price elasticit
 y and nudge effectiveness\, revealing both opportunities and risks for pub
 lic health–oriented retail design. The second essay introduces a Budget an
 d Nutrition-Aware Next Basket Recommender (BNANBR) that operationalizes pr
 ecision retailing as constraint-aware support. The system reframes persona
 lization as a welfare-relevant intervention—reducing cognitive burden whil
 e preserving autonomy and preference satisfaction. The third essay scales 
 the analysis to the population level by combining census-based synthetic p
 opulations with loyalty data. This integration produces privacy-preserving
  mosaic agents that allow ex ante simulation of retail interventions acros
 s neighborhoods and consumer segments. The results demonstrate how health-
 oriented strategies may have uneven spatial and demographic effects\, high
 lighting the need for governance mechanisms that anticipate distributional
  consequences. Together\, the essays move from diagnosis (habit as a mecha
 nism of intervention failure)\, to prescription (algorithmic tools for con
 straint-sensitive support)\, to ecosystem-level evaluation. The thesis adv
 ances precision retailing as an empirically grounded framework for improvi
 ng individual\, commercial and societal outcomes within complex retail sys
 tems.\n
DTSTART:20260130T130000Z
DTEND:20260130T150000Z
SUMMARY:PhD Research Proposal Presentation: Fares Belkhiria
URL:/desautels/channels/event/phd-research-proposal-pr
 esentation-fares-belkhiria-370591
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