TY - GEN
T1 - Data-Driven Determination and Plausibility Check of Requirement Profiles in Logistics
AU - Kohl, Markus
AU - Häring, Sandra
AU - Lopitzsch, Jens
AU - Fottner, Johannes
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
PY - 2021
Y1 - 2021
N2 - The introduction of new technologies driven by Industry 4.0 is transforming existing logistics processes. The changing tasks of the employees in this context require a systematic review of current requirement profiles (RPs) to appropriately bundle future employee tasks in homogeneous profiles. Thus, this paper develops a method for the determination of RPs taking Industry 4.0 in logistics into account. In this way, tasks are systematically transferred into RPs on the basis of similar characteristics. A data-driven method is chosen to reduce the subjectivity of the approach by using similarity factors. These reflect the central aspects of the socio-technical system and are derived from literature and practice. The method, which has been validated at a commercial vehicle manufacturer, helps in making decisions about RPs and can provide information about how eliminated, changed and new tasks affect the composition of employee RPs.
AB - The introduction of new technologies driven by Industry 4.0 is transforming existing logistics processes. The changing tasks of the employees in this context require a systematic review of current requirement profiles (RPs) to appropriately bundle future employee tasks in homogeneous profiles. Thus, this paper develops a method for the determination of RPs taking Industry 4.0 in logistics into account. In this way, tasks are systematically transferred into RPs on the basis of similar characteristics. A data-driven method is chosen to reduce the subjectivity of the approach by using similarity factors. These reflect the central aspects of the socio-technical system and are derived from literature and practice. The method, which has been validated at a commercial vehicle manufacturer, helps in making decisions about RPs and can provide information about how eliminated, changed and new tasks affect the composition of employee RPs.
KW - Classification model
KW - Clustering approach
KW - Competency
KW - HRM
KW - Industry 4.0
KW - Logistics processes
KW - Requirement profile
UR - http://www.scopus.com/inward/record.url?scp=85142303022&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-80462-6_39
DO - 10.1007/978-3-030-80462-6_39
M3 - Conference contribution
AN - SCOPUS:85142303022
SN - 9783030804619
T3 - Lecture Notes in Networks and Systems
SP - 311
EP - 319
BT - Advances in Manufacturing, Production Management and Process Control - Proceedings of the AHFE 2021 Virtual Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021
A2 - Trzcielinski, Stefan
A2 - Mrugalska, Beata
A2 - Karwowski, Waldemar
A2 - Rossi, Emilio
A2 - Di Nicolantonio, Massimo
PB - Springer Science and Business Media Deutschland GmbH
T2 - AHFE Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021
Y2 - 25 July 2021 through 29 July 2021
ER -