From disaster to flourish: how and when supply chain memory drives supply chain performance under the knowledge-based view

Purpose Despite the importance of prior knowledge in supply chain disruption management, few studies have been conducted on using such knowledge to achieve desired benefits. As such, this study aims to empirically examine the influence of supply chain memory on different dimensions of resilience capabilities (response and recovery) and their impacts on supply chain performance (SCP). Network prominence was also examined as a moderator. Design/methodology/approach Drawing from the knowledge-based view, this study uses 314 valid cross-sectional datasets from Turkish manufacturing firms to test the proposed hypotheses. The proposed hypotheses were tested using the PROCESS macro. Findings It was discovered that supply chain memory positively influences SCP, response capability and recovery capability. Response capability and recovery capability mediate the link between supply chain memory and SCP. Moreover, at a high level of network prominence, the influence of supply chain memory on response capability was further strengthened. The influence of supply chain memory on recovery capability and supply chain performance was weakened at a low level of network prominence. Originality/value The outcomes of this study advance the literature and provide a new framework for comprehending the relationships between supply chain memory, response capability, recovery capability, network prominence and SCP. The findings demonstrate how and when managers can use prior knowledge of disruptions to achieve superior SCP benefits through building resilience capabilities and network prominence.

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Publication Details

Journal
Kybernetes
Published
2025-09-04
DOI
https://doi.org/10.1108/k-11-2024-2992
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
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article

From disaster to flourish: how and when supply chain memory drives supply chain performance under the knowledge-based view

Ahmad Alzubi, Ahmed Ayad, Tolga Öz, Kolawole Iyiola
Kybernetes
Supply Chain Resilience and Risk Management
article

From disaster to flourish: how and when supply chain memory drives supply chain performance under the knowledge-based view

Ahmad Alzubi, Ahmed Ayad, Tolga Öz, Kolawole Iyiola
article en

Abstract

Purpose Despite the importance of prior knowledge in supply chain disruption management, few studies have been conducted on using such knowledge to achieve desired benefits. As such, this study aims to empirically examine the influence of supply chain memory on different dimensions of resilience capabilities (response and recovery) and their impacts on supply chain performance (SCP). Network prominence was also examined as a moderator. Design/methodology/approach Drawing from the knowledge-based view, this study uses 314 valid cross-sectional datasets from Turkish manufacturing firms to test the proposed hypotheses. The proposed hypotheses were tested using the PROCESS macro. Findings It was discovered that supply chain memory positively influences SCP, response capability and recovery capability. Response capability and recovery capability mediate the link between supply chain memory and SCP. Moreover, at a high level of network prominence, the influence of supply chain memory on response capability was further strengthened. The influence of supply chain memory on recovery capability and supply chain performance was weakened at a low level of network prominence. Originality/value The outcomes of this study advance the literature and provide a new framework for comprehending the relationships between supply chain memory, response capability, recovery capability, network prominence and SCP. The findings demonstrate how and when managers can use prior knowledge of disruptions to achieve superior SCP benefits through building resilience capabilities and network prominence.

Kybernetes
University of Mediterranean Karpasia (CY)
Openalex Percentile: Top 65%
Supply Chain Resilience and Risk Management
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