黑料网爆吃瓜

Fares Belkhiria, a doctoral student at 黑料网爆吃瓜 in the area of Marketing will be presenting his research proposal entitled:

Three Essays On Precision Retailing Across Scales: Habits, Consumer Recommendation Systems and Synthetic-Population Simulation

Friday, January 30, 2026, at 8:00am

Student Committee Chair: Professor Laurette Dub茅

Please note that the presentation will be conducted in person.

ABSTRACT

Food retail functions as a central choice infrastructure in daily life, shaping health, affordability, and wellbeing under conditions of bounded rationality, limited time, and marketing complexity. Despite this significance, health-oriented retail interventions often yield modest behavioral change. This dissertation examines why such interventions underperform and proposes a framework for precision retailing, integrating behavioral science, artificial intelligence (AI), and ecosystem modeling 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 responsible innovation. The first essay investigates how multiscale shopping habits鈥攔epetitive, cue-conditioned patterns of choice across items, categories, and stores鈥攕hape responsiveness to price promotions and health nudges. Using multi-year loyalty data and machine-learning鈥揵ased habit measures, the study demonstrates that habits systematically moderate price elasticity and nudge effectiveness, revealing both opportunities and risks for public health鈥搊riented retail design. The second essay introduces a Budget and Nutrition-Aware Next Basket Recommender (BNANBR) that operationalizes precision retailing as constraint-aware support. The system reframes personalization as a welfare-relevant intervention鈥攔educing cognitive burden while preserving autonomy and preference satisfaction. The third essay scales the analysis to the population level by combining census-based synthetic populations with loyalty data. This integration produces privacy-preserving mosaic agents that allow ex ante simulation of retail interventions across neighborhoods and consumer segments. The results demonstrate how health-oriented strategies may have uneven spatial and demographic effects, highlighting the need for governance mechanisms that anticipate distributional consequences. Together, the essays move from diagnosis (habit as a mechanism of intervention failure), to prescription (algorithmic tools for constraint-sensitive support), to ecosystem-level evaluation. The thesis advances precision retailing as an empirically grounded framework for improving individual, commercial and societal outcomes within complex retail systems.