---
title: Deep Learning Model for Newsvendor Problem with Textual Review Data
url: https://www.ml-quant.com/papers/repec/eee-proeco-v-265-y-2023-i-c-s0925527323002487/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:proeco:v:265:y:2023:i:c:s0925527323002487
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0925527323002487%3Bh%3Drepec%3Aeee%3Aproeco%3Av%3A265%3Ay%3A2023%3Ai%3Ac%3As0925527323002487
featured: 2023-11-08
citations: unknown
topic: LLMs & Text
---


# Deep Learning Model for Newsvendor Problem with Textual Review Data

The article talks about a new inventory management framework that uses a deep learning model. This model suggests order quantities based on online reviews and demand data, reducing costs by 28.7% compared to other models.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0925527323002487%3Bh%3Drepec%3Aeee%3Aproeco%3Av%3A265%3Ay%3A2023%3Ai%3Ac%3As0925527323002487
- Identifier: RePEc:eee:proeco:v:265:y:2023:i:c:s0925527323002487
- Released: 2023-11-08
- First featured: Quant Letter No. 25 (2023-11-08): https://www.ml-quant.com/issues/2023-11-08/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text

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