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Exploring the Impact of Technology 4.0 Driven Practice on Warehousing Performance: A Hybrid Approach

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  • Sadia Samar Ali

    (Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Rajbir Kaur

    (Government Girls College, Panchkula 134113, India)

Abstract

Developing a promising technology that copes with the industrial warehousing environment requires special preparation. It includes infrastructure, equipment, resources, knowledge, efficiencies, and strategies for dealing with failures. This study examines Technology 4.0 driven warehouse practices and performance based on a thorough literature review. The study presents a unique proposition as it considers a two-fold fuzzy Delphi analysis to rank the Technology 4.0 driven practices using best-worst method (BWM) based on experts’ responses. Warehouse performance measures are evaluated by the Combined Compromise Solution (CoCoSo) method. The results indicate the contributions of a ‘Man-machines or robots for facilitating human’; ‘Planning system for management’; ‘Storage systems’ as as leading practices contributing to ‘improved inventory management’, ‘effective storage and distribution’, and ‘improved distribution and shipping or delivery process’. Using this study, researchers and managers will better understand how to adopt technology in warehouse management system.

Suggested Citation

  • Sadia Samar Ali & Rajbir Kaur, 2022. "Exploring the Impact of Technology 4.0 Driven Practice on Warehousing Performance: A Hybrid Approach," Mathematics, MDPI, vol. 10(8), pages 1-22, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:8:p:1252-:d:791167
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    References listed on IDEAS

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    1. Mahroof, Kamran, 2019. "A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse," International Journal of Information Management, Elsevier, vol. 45(C), pages 176-190.
    2. K. L. Choy & G. T. S. Ho & C. K. H. Lee, 2017. "A RFID-based storage assignment system for enhancing the efficiency of order picking," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 111-129, January.
    3. Yavas, Volkan & Ozkan-Ozen, Yesim Deniz, 2020. "Logistics centers in the new industrial era: A proposed framework for logistics center 4.0," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    4. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    5. Paul J. Reaidy & A. Gunasekaran & A. Spalanzani, 2015. "Bottom-Up Approach based on Internet of things for Order Fulfillment in a Collaborative Warehousing Environment," Post-Print halshs-01374073, HAL.
    6. Tseng, Ming-Lang & Wu, Kuo-Jui & Chiu, Anthony SF. & Lim, Ming K. & Tan, Kimhua, 2018. "Service innovation in sustainable product service systems: Improving performance under linguistic preferences," International Journal of Production Economics, Elsevier, vol. 203(C), pages 414-425.
    7. Wang, Jianxin & Lim, Ming K. & Zhan, Yuanzhu & Wang, XiaoFeng, 2020. "An intelligent logistics service system for enhancing dispatching operations in an IoT environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    8. Birger Wernerfelt, 1984. "A resource‐based view of the firm," Strategic Management Journal, Wiley Blackwell, vol. 5(2), pages 171-180, April.
    9. Yong-Hong Kuo & Andrew Kusiak, 2019. "From data to big data in production research: the past and future trends," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4828-4853, August.
    10. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
    11. Li, Xiang, 2020. "Reducing channel costs by investing in smart supply chain technologies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    12. Qiu, Xuan & Luo, Hao & Xu, Gangyan & Zhong, Runyang & Huang, George Q., 2015. "Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP)," International Journal of Production Economics, Elsevier, vol. 159(C), pages 4-15.
    13. Jingjing Hao & Haoming Shi & Victor Shi & Chenchen Yang, 2020. "Adoption of Automatic Warehousing Systems in Logistics Firms: A Technology–Organization–Environment Framework," Sustainability, MDPI, vol. 12(12), pages 1-14, June.
    14. Nynke Faber & René B.M. De Koster & Ale Smidts, 2018. "Survival of the fittest: the impact of fit between warehouse management structure and warehouse context on warehouse performance," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 120-139, January.
    15. Shashank Kumar & Balkrishna E. Narkhede & Karuna Jain, 2021. "Revisiting the warehouse research through an evolutionary lens: a review from 1990 to 2019," International Journal of Production Research, Taylor & Francis Journals, vol. 59(11), pages 3470-3492, June.
    16. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    17. Reaidy, Paul J. & Gunasekaran, Angappa & Spalanzani, Alain, 2015. "Bottom-up approach based on Internet of Things for order fulfillment in a collaborative warehousing environment," International Journal of Production Economics, Elsevier, vol. 159(C), pages 29-40.
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