Improving resilience of the healthcare supply chain in a pandemic: Evidence from Europe during the COVID-19 crisis

Abstract

The severe scarcity of critical medical supplies caused by the COVID-19 pandemic led to considerable procurement challenges in the healthcare supply chain (HCSC). As ensuring the availability of such supplies during disruptions is critical, the debate on how to increase supply chain resilience in healthcare has gained new momentum. We present empirical evidence from a multi-tier case study spanning nine European medical supplies manufacturers and hospital groups. Based on the resource dependence theory, we investigated procurement-related strategies to improve medical supplies availability. We conducted semi-structured interviews with 39 procurement and supply chain management experts and derived seven propositions on buffering and bridging approaches for managing evolving resource dependencies and thereby strengthening supply chain resilience in a pandemic. Overall, we confirm the resource dependency theory's applicability for explaining companies' mitigation measures in a pandemic disruption. We find that bridging measures within the healthcare supply base, such as offering vertical procurement support for suppliers or leveraging long-term buyer-supplier relationships, are more effective for securing medical supplies than buffering measures. Complementing bridging with buffering, such as extended upstream procurement or resource sharing among hospitals, can lead to superior risk mitigation as capacities of the present supplier base may not suffice. Furthermore, we extend the resource dependence theory by showing that the severity of disruptions caused by a pandemic triggers new forms of buffering external to the HCSC. Both traditional and new buffering measures establish novel flows of medical supplies in the HCSC that can enable higher supply security in a pandemic.

Getting back into the swing of things: The adaptive path of purchasing and supply management in enhancing supply chain resilience

“… Hohenstein et al (2015) and Tukamuhabwa et al (2017) identify redundancy, collaboration, visibility, and flexibility as important antecedents to SCRES, which may also be enabled by PSM through various procurement practices. For example, these factors were used by Spieske et al (2022a) to describe the PSM role in the SCRES context within the healthcare industry. In the automotive industry, redundancy may be created by having backup suppliers and breaking up single-sourcing strategies to increase the robustness of SCs ( Belhadi et al, 2021 ).…”

A mathematical model for managing the multi-dimensional impacts of the COVID-19 pandemic in supply chain of a high-demand item

“…Among the various SC players, manufacturers, as well as retailers, are more vulnerable to simultaneous multiple disruptions such as supply, demand, and logistics disruption as a seamless flow of operations is highly critical for manufacturing supply chains (Ghadge et al, 2021 ). Relationships with suppliers have been affected, as communication is limited to audio and video calls, despite strong collaboration is more important in a crisis (Berndt, 2020 ; M. Sharma et al, 2022 ; Spieske et al, 2022 ). Moreover, the COVID-19 outbreak has caused significant product wastage, including that related to essential, high-demand food products, due to the lack of distribution facilities and the obsolescence of certain capital assets (Dente & Hashimoto, 2020 ).…”

“…Moreover, strong bonding among SC partners is also found as effective to enhance supply chain resilience during a pandemic. For example, Spieske et al, ( 2022 ) find that bridging strategies such as buyer–supplier relationships are more effective than buffering strategies. However, complementing both buffering and bridging provides superior resilience during a pandemic like the COVID-19.…”

The Important of Supply Chain Resilience During Covid-19 Pandemic For Enterprise Risk Management: A Systematic Literature Review

“…Artificial Intelligence (AI) [30] SCR reactive strategies cost / time matrix [6] Supply Chain Operational Reference (SCOR) model [31] Organizational Information Processing (OIP) theory [8] Time-to-Recovery (TTR) and Financial Impact (FI) analysis [10] Digital twin and anyLogistix simulation model [11,12] Analytical Hierarchy Process (AHP) and DEMATEL [32] Dynamic Capabilities View (DCV) [34,21] Dynamic managerial capabilities [29] Stochastic Mixed Integer Programming (MIP) model [13] Knowledge preparedness assumption [14] Proactive and reactive approach [15] Resource reconfiguration [26] Balanced capabilities and vulnerabilities [22] Collective bricolage [27] Collaboration enabler [28] Satellite imagery and blockchain technology [33] Rerpurposing barriers [23] SCR operational indicators [24] Shorter supply chains and smaller operations [25] Flexibility, readiness, integration, and response and recovery [5] ISO 14,000 [35] Resource dependence theory [16] Multi Criteria Decision Making (MCDM) and K-Means [17] Personal Protective Equipment (PPE) [19] Anticipation, adaption and respond, and recovery and learning [20] Supply Chain Alertness (SCAL) [9] Coherent Data Envelopment Analysis (CoDEA) method [18] Risk ranking of likelihood and potential impacts [1] Technology Assess impact of environmental uncertainty.…”