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Simulating the impact of digitalization on retail logistics efficiency

In: 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

Author

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  • Loske, Dominik
  • Klumpp, Matthias

Abstract

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.

Suggested Citation

  • Loske, Dominik & Klumpp, Matthias, 2020. "Simulating the impact of digitalization on retail logistics efficiency," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 77-111, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:228918
    DOI: 10.15480/882.3126
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    References listed on IDEAS

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    1. Chen, Yao & Du, Juan & Huo, Jiazhen, 2013. "Super-efficiency based on a modified directional distance function," Omega, Elsevier, vol. 41(3), pages 621-625.
    2. Ferney-Alexis Giraldo-Castrillon & Gabriel-Jaime Páramo-Bermúdez & Juan-Manuel Muñoz-Betancur, 2019. "Monitoring of Machining in the Cloud as a Cost Management Service and Follow of Cutting Parameters: Environment Developed With IoT Tools," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), IGI Global, vol. 9(3), pages 26-41, July.
    3. Salvatore T. March & Gary D. Scudder, 2019. "Predictive maintenance: strategic use of IT in manufacturing organizations," Information Systems Frontiers, Springer, vol. 21(2), pages 327-341, April.
    4. Jinjiang Wang & Lunkuan Ye & Robert X. Gao & Chen Li & Laibin Zhang, 2019. "Digital Twin for rotating machinery fault diagnosis in smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3920-3934, June.
    5. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    6. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    7. Loske, Dominic & Klumpp, Matthias, 2018. "Efficiency analysis for digitalised working systems of truck drivers," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), The Road to a Digitalized Supply Chain Management: Smart and Digital Solutions for Supply Chain Management. Proceedings of the Hamburg International C, volume 25, pages 99-119, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    8. Salvatore T. March & Gary D. Scudder, 0. "Predictive maintenance: strategic use of IT in manufacturing organizations," Information Systems Frontiers, Springer, vol. 0, pages 1-15.
    9. Kleer, Robin & Piller, Frank T., 2019. "Local manufacturing and structural shifts in competition: Market dynamics of additive manufacturing," International Journal of Production Economics, Elsevier, vol. 216(C), pages 23-34.
    10. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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