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Discussion of “Improving Inventory Management Quality with Reinforcement Learning: AI versus Human Decision-Making”

Jacob K. Thomas

Accounting Horizons2026https://doi.org/10.2308/horizons-2025-285article
AJG 3ABDC A
Weight
0.50

What the paper says

SYNOPSIS Chen, Xu, and Zhang (2025) examine the ability of reinforcement learning (RL) to improve inventory procurement, relative to two groups of human subjects: experienced CPAs in a lab environment and employees at Fujian Tianma Science and Technology Group Co. (Tianma) engaged in procurement of raw materials. Although the study concludes that RL outperforms humans, I discuss two sets of questions—about inventory management and about AI—that readers might raise regarding the conclusion. Data Availability: Data are taken from the discussed article. JEL Classifications: C52; D25; M11; M41.

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https://doi.org/https://doi.org/10.2308/horizons-2025-285

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@article{jacob2026,
  title        = {{Discussion of “Improving Inventory Management Quality with Reinforcement Learning: AI versus Human Decision-Making”}},
  author       = {Jacob K. Thomas},
  journal      = {Accounting Horizons},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.2308/horizons-2025-285},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.