⌘+K

Pulse Explore Communities Researchers Journals

Browser extensionInstagram

Home Communities Explore

January 1, 2026IEEE AccessOpen Access

Corrections to “Demand Forecasting in Data-Scarce and Resource-Restricted Environments”

David Gögelein Marianne von Schwerin Thomas Walter

View Full Paper

Ask AI

Bookmark

Share

Key Points

This document corrects inaccuracies identified in previous demand forecasting models tailored for data-scarce and resource-restricted environments.
Reviewed original forecasting models
Identified and documented inaccuracies
Proposed adjustments to improve model robustness
Several key inaccuracies found in initial model configurations
Recommended corrections aim to enhance forecasting accuracy
Implications for future applications of forecasting in similar environments are discussed

Ask about this paper

Answers are grounded in this paper and cite their sources.

Ask your own question…

Implication

Corrections address inaccuracies in demand forecasting models for data-scarce settings, indicating important adjustments for accuracy.

Abstract

Presents corrections to the paper, (Demand Forecasting in Data-Scarce and Resource-Restricted Environments).

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Gögelein et al. (2026) studied this question.

synapsesocial.com/papers/69fd7d4abfa21ec5bbf05c8a https://doi.org/10.1109/access.2026.3687724

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 10 related papers. Consider them for comparative context:

1Supplementary materials for the paper: Selective LLM Revision with Statistical Calibration for Sparse Retail Demand ForecastingOriginal Research · 2026
2Erratum to “Multicriteria Course Mode Selection and Classroom Assignment Under Sudden Space Scarcity”Original Research · 2026
3Demand Hidden by Stockouts: Censored Demand Recovery and Green Waste-Reduction Forecasting for Sustainable Fresh-Food Consumption Under Emerging-Market UrbanizationHuman Clinical Trial · 2026
4Propagation of best practices in value and supply chain management: Demand forecasting and planning2024
5The demand planning renaissance: A data-driven approach2024 · 2 citations
6RETRACTION: The impact of sustainable development strategy on sustainable supply chain firm performance in the digital transformation era2024 · 1 citations
7A distribution-free newsvendor model considering environmental impact and shortages with price-dependent stochastic demandOriginal Research · 2022 · 9 citations
8Correction to: 9 papers to add missing data availability statementsOriginal Research · 2026 · 1 citations
9Graph Signal Processing Based Epileptic Seizure Event and its Onset Detection from Multi-Channel EEG SignalsIEEE Access · 2026
10Myocardial Infarction Detection from 12-Lead ECG Signals Using a Hybrid CNN-BiLSTM Deep Learning ModelIEEE Access · 2026

More from IEEE Access

More from Technische Hochschule Ulm