Experimental Designs for Multi-Item Multi-Period Inventory Control
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910006896492544 |
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| author | Chen, Xinqi Bai, Xingyu Zheng, Zeyu Si, Nian |
| author_facet | Chen, Xinqi Bai, Xingyu Zheng, Zeyu Si, Nian |
| contents | 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, namely, 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, proving that switchback designs systematically underestimate, while item-level randomization systematically overestimate, the global treatment effect. Motivated by two-sided randomization, we propose a pairwise design over items and time and analyze its bias properties. Numerical experiments using real-world data validate our theory and provide concrete guidance for selecting experimental designs in practice. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2501_11996 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Experimental Designs for Multi-Item Multi-Period Inventory Control Chen, Xinqi Bai, Xingyu Zheng, Zeyu Si, Nian Methodology Econometrics 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, namely, 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, proving that switchback designs systematically underestimate, while item-level randomization systematically overestimate, the global treatment effect. Motivated by two-sided randomization, we propose a pairwise design over items and time and analyze its bias properties. Numerical experiments using real-world data validate our theory and provide concrete guidance for selecting experimental designs in practice. |
| title | Experimental Designs for Multi-Item Multi-Period Inventory Control |
| topic | Methodology Econometrics |
| url | https://arxiv.org/abs/2501.11996 |