Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.3136
Publisher URL: https://www.epubli.de/shop/buch/Data-Science-and-Innovation-in-Supply-Chain-Management-Wolfgang-Kersten-9783753123462/106047
Title: Evaluation of data quality in dimensioning capacity
Language: English
Authors: Vliegen, Lea 
Moroff, Nikolas Ulrich 
Riehl, Katharina 
Editor: Kersten, Wolfgang 
Blecker, Thorsten 
Ringle, Christian M.  
Keywords: Logistics;Industry 4.0;Digitalization;Innovation;Supply Chain Management;Artificial Intelligence;Data Science
Issue Date: 23-Sep-2020
Source: Hamburg International Conference of Logistics (HICL) 29: 355-394 (2020)
Part of Series: Proceedings of the Hamburg International Conference of Logistics (HICL) 
Volume number: 29
Abstract (english): 
Purpose: This paper aims to give an overview of the current state of research on measuring data quality. The identified methods will be applied to the task of dimen-sioning capacities (e.g. warehouse capacities) in the field of supply chain design (SCD) to further increase trust in decision support and to make full use of the poten-tial of analytics. Methodology: The data requirements for SCD decisions are identified through the combination of findings of a research project and additional literature research. Moreover, an overview on measuring data quality will be given according to a litera-ture study. Based on the required data, the applicability of methods to measure data quality will be analyzed and an application concept developed. Findings: The quality of decisions can only be as good as the quality of the data they are based on. The article provides an overview of methods for evaluating datasets and develops an approach for measuring and evaluating data quality for the specific case of capacities in the SCD process. Originality: The adaption of approaches of measuring data quality to the problem of dimensioning capacities in SCD ensures an adequate evaluation of whether the data fulfills the required quality for the planning tasks.
Conference: Hamburg International Conference of Logistics (HICL) 2020 
URI: http://hdl.handle.net/11420/8041
DOI: 10.15480/882.3136
ISBN: 978-3-753123-46-2
ISSN: 2365-5070
Document Type: Chapter/Article (Proceedings)
License: CC BY-SA 4.0 (Attribution-ShareAlike 4.0) CC BY-SA 4.0 (Attribution-ShareAlike 4.0)
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