Logistics 4.0 measurement model: empirical validation based on an international survey

• Published in: Industrial management + data systems 2022-05, Vol.122 (5), p.1384-1409
• Main Authors: Dallasega, Patrick, Woschank, Manuel, Sarkis, Joseph, Tippayawong, Korrakot Yaibuathet
• Format: Article
• Language: English
• Subjects: Automotive supplies; Best practice; Collaboration; Empirical analysis; Enterprise resource planning; Focus groups; Industry 4.0; Information systems; Innovations; Internet of Things; Inventory control; Investigations; Literature reviews; Logistics; Manufacturing; Production controls; Radio frequency identification; Supply chains; Sustainability
• ISSN: 0263-5577; 1758-5783
• DOI: 10.1108/IMDS-11-2021-0694

PurposeThis study aims to provide a measurement model, and the underlying constructs and items, for Logistics 4.0 in manufacturing companies. Industry 4.0 technology for logistics processes has been termed Logistics 4.0. Logistics 4.0 and its elements have seen varied conceptualizations in the literature. The literature has mainly focused on conceptual and theoretical studies, which supports the notion that Logistics 4.0 is a relatively young area of research. Refinement of constructs and building consensus perspectives and definitions is necessary for practical and theoretical advances in this area.Design/methodology/approachBased on a detailed literature review and practitioner focus group interviews, items of Logistics 4.0 for manufacturing enterprises were further validated by using a large-scale survey with practicing experts from organizations located in Central Europe, the Northeastern United States of America and Northern Thailand. Exploratory and confirmatory factor analyses were used to define a measurement model for Logistics 4.0.FindingsBased on 239 responses the exploratory and confirmatory factor analyses resulted in nine items and three factors for the final Logistics 4.0 measurement model. It combines “the leveraging of increased organizational capabilities” (factor 1) with “the rise of interconnection and material flow transparency” (factor 2) and “the setting up of autonomization in logistics processes” (factor 3).Practical implicationsPractitioners can use the proposed measurement model to assess their current level of maturity regarding the implementation of Logistics 4.0 practices. They can map the current state and derive appropriate implementation plans as well as benchmark against best practices across or between industries based on these metrics.Originality/valueLogistics 4.0 is a relatively young research area, which necessitates greater development through empirical validation. To the best of the authors knowledge, an empirically validated multidimensional construct to measure Logistics 4.0 in manufacturing companies does not exist.