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Loske, Dominik
Klumpp, Matthias
Year of Publication: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29 [ISBN:] 978-3-7531-2346-2 [Year:] 2020 [Pages:] 77-111
Purpose: The study uses the results of an efficiency analysis for digitalization within a retail logistics blue-collar work system of professional truck drivers and aims to elaborate an ex-ante efficiency simulation approach for digitalization scenarios. Methodology: The simulation method combines the efficiency scores of Data Envelopment Analysis (DEA), statistical bootstrapping, and regression analysis. By increas-ing the original sample size of n=30 truck drivers up to 60,000 samples through 2,000 bootstrap iterations, it is possible to gain a highly significant regression function. Findings: The mathematical simulation approach can be transferred to alternate scenarios in terms of forecasting efficiency development based on the experience distribution of the workforce. Originality: As the impact of digitalization on the efficiency of blue-collar work systems is often unknown, this methodology could provide insights for logistics researchers and managers when estimating the efficiency impact of digitalization.
Industry 4.0
Supply Chain Management
Artificial Intelligence
Data Science
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Document Type: 
Conference Paper

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