The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/21293733

Julian Maas (2023): Software code in R for a cluster analysis to cluster and characterize autonomous last mile concepts in a standardized and holistic manner. Version 2. 4TU.ResearchData. software. https://doi.org/10.4121/21293733.v2

Version 1 - 2022-10-10

Usage statistics

Categories

• Ground Transport
• Transport

Keywords

autonomous fulfillment concepts autonomous last mile concepts Cluster Analysis

Licence

CC BY 4.0

Export as...

RefWorks BibTeX Reference Manager Endnote DataCite NLM DC CFF

by Julian Maas

This file is the softwarecode in R for a clusteranalysis to cluster and characterize autonomous last mile concepts in a standardized and holistic manner.

With the developed clusters it is possible to better categorize and compare individual autonomous last mile concepts. Furthermore, the developed taxonomy of autonomous last mile concepts and the cluster analysis allow an evaluation of the interrelations between characteristics of autonomous last mile concepts, so that the design of new concepts as well as the adaptation or selection of a concept for a specific use case is supported.

History

• 2022-10-10 first online

• 2023-03-23 published, posted

Publisher

4TU.ResearchData

Format

rmd

Data link

https://doi.org/10.4121/21293736

Organizations

TU Berlin, Department of Logistics