Facilitating artificial intelligence powered supply chain analytics through alliance management during the pandemic crises in the B2B context

Dubey, Rameshwar, Bryde, David J, Blome, Constantin, Roubaud, David and Giannakis, Mihalis (2021) Facilitating artificial intelligence powered supply chain analytics through alliance management during the pandemic crises in the B2B context. Industrial Marketing Management, 96. pp. 135-146. ISSN 0019-8501

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Abstract

The COVID-19 pandemic has disrupted global supply chains and exposed weak links in the chains far beyond what most people have witnessed in their living memory. The scale of disruption affects every nation and industry, and the sudden and dramatic changes in demand and supply that have occurred during the pandemic crisis clearly differentiate its impact from other crises. Using the dynamic capabilities view, we studied alliance management capability (AMC) and artificial intelligence (AI) driven supply chain analytics capability (AI-SCAC) as dynamic capabilities, under the moderating effect of environmental dynamism. We tested our four research hypotheses using survey data collected from the Indian auto components manufacturing industry. For data analysis we used Warp PLS 7.0 (a variance-based structural equation modelling tool). We found that alliance management capability under the mediating effect of artificial intelligence-powered supply chain analytics capability enhances the operational and financial performance of the organization. Moreover, we also observed that the alliance management capability has a significant effect on artificial intelligence-powered supply chain analytics capability under the moderating effect of environmental dynamism. The results of our study provide a nuanced understanding of the dynamic capabilities and the relational view of organization. Finally, we noted the limitations of our study and provide numerous research directions that may help answer some of the questions that arise from our study.

Item Type: Article
Schools and Departments: University of Sussex Business School > Management
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 03 Jun 2021 07:56
Last Modified: 03 Jun 2021 09:15
URI: http://sro.sussex.ac.uk/id/eprint/99558

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