Clustering and Classification of Manufacturing Enterprises Regarding Their Industry 4.0 Reshoring Incentives

P. Unterberger, J.M. Müller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Due to drivers like Industry 4.0, reshoring recently receives more attention. In order to increase understanding, in this novel field of research, k-means clustering is performed to find groups of enterprises, which differ regarding their reshoring incentives. Based on these clusters, manufacturing enterprises are classified by the combination of an intra variance analysis and prior knowledge. Therefore, an own enlarged sample, encompassing 94 German industrial enterprises with global sourcing and production activities is used. It is investigated that five clusters segment the sample optimally and that the importance of innovation as well as trust and sustainability are decisive for the classification of German manufacturing enterprises regarding their reshoring incentives. These findings contribute to the body of knowledge about reshoring incentives in terms of methodology and content, since unsupervised learning is used for the first time within that context and enables insight into previously unexplored structures of the reshoring phenomenon. © 2021 Elsevier B.V.. All rights reserved.
Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020)
PublisherElsevier B.V.
Pages696-705
Number of pages10
DOIs
Publication statusPublished - 2021
Event2nd International Conference on Industry 4.0 and Smart Manufacturing, ISM 2020 - Virtual
Duration: 23 Nov 202025 Nov 2020
https://www.msc-les.org/ism2020/

Conference

Conference2nd International Conference on Industry 4.0 and Smart Manufacturing, ISM 2020
Abbreviated titleISM 2020
Period23/11/2025/11/20
Internet address

Keywords

  • Industry 4.0
  • K-Means Clustering
  • Reshoring
  • Unsupervised Learning
  • Flow control
  • Body of knowledge
  • German manufacturing
  • Global sourcing
  • Industrial enterprise
  • Manufacturing enterprise
  • Prior knowledge
  • Production activity
  • Variance analysis
  • K-means clustering

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