AI technologies and their impact on supply chain resilience during COVID-19
International Journal of Physical Distribution & Logistics Management
; 52(2):130-149, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1713870
ABSTRACT
Purpose>COVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approach>We adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.Findings>An AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implications>As the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implications>Supply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/value>The present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.
Transportation--Trucks And Trucking; Artificial intelligence; Supply chain resilience; COVID-19; Organisational information processing theory; Raw materials; Manufacturing; Chain dynamics; Data processing; Consumers; Information systems; Resilience; Failure modes; Pandemics; Supply chains; Information processing; Failure analysis; Constraint modelling; Coronaviruses; Contingency; Trade restrictions; Suppliers; 42511:Business to Business Electronic Markets
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Type of study:
Experimental Studies
Language:
English
Journal:
International Journal of Physical Distribution & Logistics Management
Year:
2022
Document Type:
Article
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