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Evaluation of data quality in dimensioning capacity
Citation Link: https://doi.org/10.15480/882.3136
Publikationstyp
Conference Paper
Date Issued
2020-09-23
Sprache
English
Herausgeber*innen
TORE-DOI
TORE-URI
First published in
Number in series
29
Start Page
355
End Page
394
Citation
Hamburg International Conference of Logistics (HICL) 29: 355-394 (2020)
Contribution to Conference
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.
Subjects
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
DDC Class
330: Wirtschaft
Publication version
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Vliegen et al. (2020) - Evaluation of Data Quality in Dimensioning Capacity.pdf
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1.24 MB
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