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Experimental Designs for Multi-Item Multi-Period Inventor...
[Submitted on 21 Jan 2025 (v1), last revised 17 Jun 2026 (this v · 2026-06-18 · via stat updates on arXiv.org

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Abstract:Randomized experiments, or A/B testing, are the gold standard for evaluating interventions, yet they remain underutilized in inventory management. This study addresses this gap by analyzing A/B testing strategies in multi-item, multi-period inventory systems with lost sales and capacity constraints. We examine two canonical experimental designs--switchback experiments and item-level randomization--and show that both suffer from systematic bias due to interference: temporal carryover in switchbacks and cannibalization across items under capacity constraints. Under mild conditions, we characterize the direction of this bias in different scenarios. Motivated by two-sided randomization, we propose a pairwise design over items and time and analyze its bias properties. Controlled stochastic simulations verify the theoretical predictions, and trace-driven experiments on real-world fresh-retail data show that the same mechanisms persist in realistic environments with stockout substitution.

Submission history

From: Nian Si [view email]
[v1] Tue, 21 Jan 2025 09:37:14 UTC (2,489 KB)
[v2] Sat, 31 Jan 2026 06:36:06 UTC (1,223 KB)
[v3] Wed, 17 Jun 2026 00:50:12 UTC (335 KB)