Fabian Taigel

University of Wuerzburg, Chair of Logistics and Quantitative Methods

Sanderring 2

Wuerzburg, D-97070

Germany

SCHOLARLY PAPERS

4

DOWNLOADS
Rank 40,365

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Top 40,365

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2,408

SSRN CITATIONS

2

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0

Scholarly Papers (4)

1.

Machine Learning for Inventory Management: Analyzing Two Concepts to Get From Data to Decisions

Number of pages: 40 Posted: 21 Oct 2018 Last Revised: 08 Nov 2019
Jan Meller and Fabian Taigel
University of Wuerzburg - Chair of Logistics and Quantitative Methods and University of Wuerzburg, Chair of Logistics and Quantitative Methods
Downloads 1,261 (31,939)

Abstract:

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Inventory Management, Machine Learning, Newsvendor

2.

Prescriptive Analytics for Inventory Management: A Comparison of New Approaches

Number of pages: 50 Posted: 22 Aug 2018
Jan Meller, Fabian Taigel and Richard Pibernik
University of Wuerzburg - Chair of Logistics and Quantitative Methods, University of Wuerzburg, Chair of Logistics and Quantitative Methods and University of Würzburg - Business Administration & Economics
Downloads 519 (104,857)

Abstract:

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Prescriptive Analytics, Inventory Management, SEP Newsvendor Model, Machine Learning, Tree-Based Regression, Linear Quantile Regression

3.

Model Mis-Specification in Newsvendor Decisions: A Comparison of Frequentist Parametric, Bayesian Parametric and Nonparametric Approaches

Number of pages: 32 Posted: 01 Jan 2020 Last Revised: 22 Jun 2020
Gah‐Yi Ban, Zhenyu Gao and Fabian Taigel
Imperial College Business School, Tsinghua University and University of Wuerzburg, Chair of Logistics and Quantitative Methods
Downloads 517 (105,639)

Abstract:

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data-driven decision-making, newsvendor, inventory, model mis-specification, asymptotic statistics

4.

Prescriptive Call Center Staffing

Number of pages: 40 Posted: 04 Jun 2020
Fabian Taigel and Jan Meller
University of Wuerzburg, Chair of Logistics and Quantitative Methods and University of Wuerzburg - Chair of Logistics and Quantitative Methods
Downloads 111 (469,750)

Abstract:

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Capacity Management, Machine Learning, Call Center, Fluid model,