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Estimating the Intensity of Cargo Flows in Warehouses by Applying Guanxi Principles

Author

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  • Veslav Kuranovič

    (Department of Logistics and Transport Management, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Plytinės g. 25, LT-10105 Vilnius, Lithuania)

  • Edgar Sokolovskij

    (Department of Automobile Engineering, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Plytinės g. 25, LT-10105 Vilnius, Lithuania)

  • Darius Bazaras

    (Department of Logistics and Transport Management, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Plytinės g. 25, LT-10105 Vilnius, Lithuania)

  • Aldona Jarašūnienė

    (Department of Logistics and Transport Management, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Plytinės g. 25, LT-10105 Vilnius, Lithuania)

  • Kristina Čižiūnienė

    (Department of Logistics and Transport Management, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Plytinės g. 25, LT-10105 Vilnius, Lithuania)

Abstract

Proper supply chain management helps to ensure business continuity considering the increased importance of globalization. Logistics processes play an important role in keeping the supply chain running smoothly, and warehouse management is one of the most important logistics activities. The movement of freight flows in the supply chain poses many challenges to the arrangement of sustainable processes at the international level. The stopping of these flows at warehouses and/or terminals temporarily and/or for longer periods of time is yet another challenge. In this respect, a number of analyses and studies have been conducted in the scientific literature to identify the most serious and frequent problems: lack of planning of work activities, partial accounting of the work performed, lack of timely accounting of the internal movement of goods within the warehouse, absence of a spare-parts management system, etc. On the other hand, warehousing processes have been analysed to identify certain efficiency gaps in freight flows within warehouses; thus, this article addresses this problem by applying guanxi principles. Using guanxi theory and practice to test various assumptions for efficient freight flow movement in warehouses, a study was conducted using quantitative and qualitative methods and expert judgment. Based on the results of the conducted empirical studies, guanxi philosophy can be concluded to have an impact on the efficient management of warehouse processes when goods are removed from a warehouse over 365 days with an annual daily loading flow rate of 103,490 t/m and a loading density of 280 kg/m 3 . This indicates that the application of guanxi principles is important, which reflects the intensity of the logistics processes of cargo flows and transport dynamics between guanxi and warehouse optimization.

Suggested Citation

  • Veslav Kuranovič & Edgar Sokolovskij & Darius Bazaras & Aldona Jarašūnienė & Kristina Čižiūnienė, 2023. "Estimating the Intensity of Cargo Flows in Warehouses by Applying Guanxi Principles," Sustainability, MDPI, vol. 15(23), pages 1-22, November.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16226-:d:1286010
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    References listed on IDEAS

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    1. Letitia M. Pohl & Russell D. Meller & Kevin R. Gue, 2009. "Optimizing fishbone aisles for dual‐command operations in a warehouse," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(5), pages 389-403, August.
    2. Petersen, Charles G. & Aase, Gerald, 2004. "A comparison of picking, storage, and routing policies in manual order picking," International Journal of Production Economics, Elsevier, vol. 92(1), pages 11-19, November.
    3. Chu, Zhaofang & Feng, Bo & Lai, Fujun, 2018. "Logistics service innovation by third party logistics providers in China: Aligning guanxi and organizational structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 291-307.
    4. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    5. Dongping Song, 2021. "A Literature Review, Container Shipping Supply Chain: Planning Problems and Research Opportunities," Logistics, MDPI, vol. 5(2), pages 1-26, June.
    6. Li, Po-Chien & Lin, Bou-Wen, 2006. "Building global logistics competence with Chinese OEM suppliers," Technology in Society, Elsevier, vol. 28(3), pages 333-348.
    7. de Koster, Rene & Le-Duc, Tho & Roodbergen, Kees Jan, 2007. "Design and control of warehouse order picking: A literature review," European Journal of Operational Research, Elsevier, vol. 182(2), pages 481-501, October.
    8. Bartolini, M. & Bottani, E. & Grosse, E. H., 2019. "Green warehousing: systematic literature review and bibliometric analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 112369, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Chu, Zhaofang & Wang, Qiang & Lai, Fujun & Collins, Brian J., 2019. "Managing interdependence: Using Guanxi to cope with supply chain dependency," Journal of Business Research, Elsevier, vol. 103(C), pages 620-631.
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