Loske, DominikDominikLoskeKlumpp, MatthiasMatthiasKlumpp2020-12-012020-12-012020-09-23Hamburg International Conference of Logistics (HICL) 29: 77-111 (2020)http://hdl.handle.net/11420/8016Purpose: 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 Envel-opment 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 sys-tems is often unknown, this methodology could provide insights for logistics re-searchers and managers when estimating the efficiency impact of digitalization.enhttps://creativecommons.org/licenses/by-sa/4.0/logisticsIndustry 4.0digitalizationInnovationsupply chain management;Artificial Intelligencedata scienceWirtschaftHandel, Kommunikation, VerkehrConference Paper10.15480/882.3126https://www.epubli.de/shop/buch/Data-Science-and-Innovation-in-Supply-Chain-Management-Wolfgang-Kersten-9783753123462/10604710.15480/882.3126Kersten, WolfgangWolfgangKerstenBlecker, ThorstenThorstenBleckerRingle, Christian M.Christian M.RingleOther