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Logistics 4.0: a systematic review towards a new logistics system

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  • Sven Winkelhaus
  • Eric H. Grosse

Abstract

Enterprises are confronted with new customer requirements and challenged by global competition leading to fundamental changes of today’s industry. Against this background, at present Industry 4.0 is the main concept of dealing with these challenges in manufacturing. Lacking a comparable covering concept in logistics, this study aims to stringently unify diverse approaches in research to a Logistics 4.0-framework in order to generate a new picture of the state of logistics research. In this article, a comprehensive framework of Logistics 4.0 is developed. First, the term Logistics 4.0 is defined, and then a systematic literature review of 114 articles on Logistics 4.0 is performed. The resulting framework combines external triggers, main technological innovations, impacts of human interactions and logistics tasks. Existing solutions that support Logistics 4.0 are summarised according to the technologies: internet of things, cyber-physical systems, Big Data, cloud computing, mobile-based systems, social media-based systems and further technologies. Managerial implications are outlined and open research issues are examined. For researchers, this review offers the possibility to unify and expand existing solutions and to identify links and interfaces that are still needed. As for managerial implications, this framework can be used to identify future strategies and technologies to fulfil certain logistics tasks, but also to develop new technological solutions for current and future demands.

Suggested Citation

  • Sven Winkelhaus & Eric H. Grosse, 2020. "Logistics 4.0: a systematic review towards a new logistics system," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 18-43, January.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:1:p:18-43
    DOI: 10.1080/00207543.2019.1612964
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    Citations

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    Cited by:

    1. Anna Saniuk, 2022. "The Logistics 4.0 Implementation Supported by the Balanced Scorecard Method," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 198-207.
    2. Kabadurmus, Ozgur & Kayikci, Yaşanur & Demir, Sercan & Koc, Basar, 2023. "A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    3. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    4. Brauner, Philipp & Ziefle, Martina, 2022. "Beyond playful learning – Serious games for the human-centric digital transformation of production and a design process model," Technology in Society, Elsevier, vol. 71(C).
    5. Yalcin, Haydar & Daim, Tugrul U., 2022. "Logistics, supply chain management and technology research: An analysis on the axis of technology mining," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    6. Menti, Federica & Romero, David & Jacobsen, Peter, 2023. "A technology assessment and implementation model for evaluating socio-cultural and technical factors for the successful deployment of Logistics 4.0 technologies," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    7. Chung, Sai-Ho, 2021. "Applications of smart technologies in logistics and transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    8. Cannavacciuolo, Lorella & Ferraro, Giovanna & Ponsiglione, Cristina & Primario, Simonetta & Quinto, Ivana, 2023. "Technological innovation-enabling industry 4.0 paradigm: A systematic literature review," Technovation, Elsevier, vol. 124(C).
    9. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    10. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    11. Cui, Huixia & Chen, Xiangyong & Guo, Ming & Jiao, Yang & Cao, Jinde & Qiu, Jianlong, 2023. "A distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    12. Chen, Yi-Ting & Sun, Edward W. & Chang, Ming-Feng & Lin, Yi-Bing, 2021. "Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0," International Journal of Production Economics, Elsevier, vol. 238(C).
    13. Farajpour, Farnoush & Hassanzadeh, Alireza & Elahi, Shaban & Ghazanfari, Mehdi, 2022. "Digital supply chain blueprint via a systematic literature review," Technological Forecasting and Social Change, Elsevier, vol. 184(C).

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