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Digital supply chain transformation: effect of firm’s knowledge creation capabilities under COVID-19 supply chain disruption risk
Operations Management Research ; : 1-16, 2022.
Article in English | EuropePMC | ID: covidwho-2073514
ABSTRACT
Digital supply chain (SC) transformation has emerged as a way to improve information sharing, better manage demand, and reduce costs in supply chain management. However, the majority of firms are unable to transform their supply chains into digital models. Thus, this study aims to identify the key drivers of digital SC transformation and provide empirical evidence on the extent to which firms’ knowledge creation capabilities could impact firms’ level of digital supply chain transformation. Based on a knowledge-based view, this study proposes that firms’ knowledge creation capabilities – which consist of the capacity to absorb external knowledge and the intent to learn with partners within the SC – are crucial to the successful knowledge transfer required to digitially transform, particularly under the effects of COVID-19 supply chain disruption risks. Survey data collected from 923 Vietnamese firms participating in cross-border trades were analyzed using partial least squares structural equation modeling (PLS-SEM). This study finds that firms’ absorptive capacity and learning intent are critical drivers of their digital supply chain transformation. Moreover, the high uncertainties in external environments are found to substantially accelerate the digital transformation processes and influence the effectiveness of firms’ knowledge creation capabilities in digital SC transformation. Significantly, firms are more inclined toward external knowledge sources to cope with disruption risks in the supply chain. This study contributes a novel approach to better understanding the role of knowledge creation capabilities in responding to supply chain disruption risks and fills a gap in research on drivers of successful digital SC transformation.
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Collection: Databases of international organizations Database: EuropePMC Type of study: Experimental Studies / Prognostic study Language: English Journal: Operations Management Research Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: EuropePMC Type of study: Experimental Studies / Prognostic study Language: English Journal: Operations Management Research Year: 2022 Document Type: Article