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A Network Maturity Mapping Tool for Demand-Driven Supply Chain Management: A Case for the Public Healthcare Sector

Author

Listed:
  • Munyaradzi Bvuchete

    (Department of Industrial Engineering, Stellenbosch University, Stellenbosch 7600, South Africa)

  • Sara Saartjie Grobbelaar

    (DST-NRF Centre of Excellence in Scientometrics and Science, Technology and Innovation Policy (SciSTIP), Stellenbosch University, Stellenbosch 7600, South Africa)

  • Joubert van Eeden

    (Department of Industrial Engineering, Stellenbosch University, Stellenbosch 7600, South Africa)

Abstract

The healthcare supply chain is a complex adaptive ecosystem that facilitates the delivery of health products to the end patient in a cost-effective way. However, low forecast accuracy and high demand volatility in healthcare supply chains have resulted in an increase in stockouts, operational inefficiencies, poor health outcomes, and a significant increase in supply chain costs. To cope with these challenges, organisations are trying to adopt demand-driven supply chain management (DDSCM) operating practices which have been established in other sectors such as the telecommunications, fruit, and flower industries. However, previous studies have not considered these practices in the healthcare industry, and hence no methodologies exist that support the implementation of these practices in this context. Moreover, current studies present cases where the focus has been on improving and expanding individual organisational performance, but no supply chain network-level studies exist on the healthcare industry. Therefore, this paper provides a network-level analysis when addressing DDSCM in the healthcare industry. A grounded theory-based approach coupled with a conceptual framework analysis process was used to leverage a systematized literature review methodology with the development of a network maturity mapping tool for DDSCM which was validated in the public healthcare sector.

Suggested Citation

  • Munyaradzi Bvuchete & Sara Saartjie Grobbelaar & Joubert van Eeden, 2021. "A Network Maturity Mapping Tool for Demand-Driven Supply Chain Management: A Case for the Public Healthcare Sector," Sustainability, MDPI, vol. 13(21), pages 1-29, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11988-:d:668059
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    1. Davidson de Almeida Santos & Osvaldo Luiz Gonçalves Quelhas & Carlos Francisco Simões Gomes & Luis Perez Zotes & Sérgio Luiz Braga França & Guilherme Vinagre Pinto de Souza & Robson Amarante de Araújo, 2020. "Proposal for a Maturity Model in Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(22), pages 1-37, November.
    2. Nunzia Carbonara & Roberta Pellegrino, 2018. "Real options approach to evaluate postponement as supply chain disruptions mitigation strategy," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5249-5271, August.
    3. Mukesh Kumar & Jag Srai & Luke Pattinson & Mike Gregory, 2013. "Mapping of the UK food supply chains: capturing trends and structural changes," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 10(2), pages 299-326, August.
    4. Bonney, M. C. & Zhang, Zongmao & Head, M. A. & Tien, C. C. & Barson, R. J., 1999. "Are push and pull systems really so different?," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 53-64, March.
    5. Wallace J. Hopp & Mark L. Spearman, 2004. "To Pull or Not to Pull: What Is the Question?," Manufacturing & Service Operations Management, INFORMS, vol. 6(2), pages 133-148, August.
    6. Felipe Caro & Jérémie Gallien, 2010. "Inventory Management of a Fast-Fashion Retail Network," Operations Research, INFORMS, vol. 58(2), pages 257-273, April.
    7. Meisam Nasrollahi & Jafar Razmi, 2021. "A mathematical model for designing an integrated pharmaceutical supply chain with maximum expected coverage under uncertainty," Operational Research, Springer, vol. 21(1), pages 525-552, March.
    8. Mendes, Paulo & Leal, José Eugênio & Thomé, Antônio Márcio Tavares, 2016. "A maturity model for demand-driven supply chains in the consumer product goods industry," International Journal of Production Economics, Elsevier, vol. 179(C), pages 153-165.
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    1. Beata Skowron-Grabowska & Marta Wincewicz-Bosy & Małgorzata Dymyt & Adam Sadowski & Tomasz Dymyt & Katarzyna Wąsowska, 2022. "Healthcare Supply Chain Reliability: The Case of Medical Air Transport," IJERPH, MDPI, vol. 19(7), pages 1-18, April.

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