Table 4.

The role of digital technologies in building supply chain resilience to COVID-19 disruption, as portrayed in the literature

Technologies	Applications	Findings		Sources
		Effect of technology	Impact on another potential pandemic
Internet of Things (IoT)	• IoT-enabled production lines • IoT-enabled delivery	Flexibility	Some disruptions can be avoided or reduced by enabling more flexible production capacity and better utilisation of inventory and logistics processes	Agrawal et al (2020).; DeAngelis (2020); De Sousa Jabbour et al. (2020); George et al. (2020); Johnson (2020b); Kilpatrick and Barter (2020); Kumar et al. (2020); Lin and Lanng (2020); Sharma et al. (2020a; b); Zhu et al. (2020)
Automation	• Robotics (physical automation) in manufacturing and warehousing • Automated Guided Vehicles (AGV) • Process Automation (data collection, quality control, inspection)	Flexibility	Some disruptions can be avoided by supplementing or replace labour capacity in manufacturing and delivery, thereby reducing infections and potential stops in the supply chain flow of material	Agrawal et al. (2020); Belhadi et al. (2020); Cahn (2020); Chowdhury et al. (2020); De Sousa Jabbour et al. (2020); Liuima (2020a); George et al. (2020); Shih (2020); Szakonyi (2020)
3D Printing	• Production of spare parts • Manufacturing of customised products • Feasible for complex, low-volume parts, not for mass manufacturing.	Flexibility	Some disruptions can be avoided by enabling in-house production of complex, low-volume spare parts and customized products which will reduce the need for transportation/travel through enabling production closer to the customer, as well as reducing dependency on suppliers	Liuima (2020a); Kilpatrick and Barter (2020); Kumar et al. (2020); Queiroz et al. (2020); Shih (2020)
Augmented reality	• Remote assistance in equipment instalment, maintenance	Flexibility Collaboration	Some disruptions can be avoided by enabling remote assistance in equipment installation and maintenance, replacing the need for travel in times where borders are closed or travel constrained	Agrawal et al. (2020); De Sousa Jabbour et al. (2020)
Traceability technologies	• RFID tags • Blockchain • Cell phone geolocation • Satellites • Drones	Visibility Collaboration	Some disruptions can be avoided by enabling better knowledge about the location of products and capacity in real-time, as well as by using real-time demand information and direct information exchange with supplier and customers	Agrawal et al. (2020); Belhadi et al. (2020); Raghu (2020); Cordon and Buatois (2020); George et al. (2020); Johnson (2020a, b); Kilpatrick and Barter (2020); Quayson et al. (2020); Queiroz et al. (2020); Sharma A et al. (2020a, 2020b)
Artificial intelligence Machine learning Advanced Analytics	• Demand forecasting • Planning • Prediction • Process automation • Digital manufacturing	Risk management Visibility	Some disruptions can be avoided due to increased support to disruption decision making and recovery. Demand shocks can be better detected. Disruptions can be better anticipated (early warning). The impact of the disruption can be better assessed. Also, recovery after a pandemic caused disruption can be strengthened because of improved demand re-planning capability	Agrawal et al. (2020); Alicke et al. (2020); Belhadi et al. (2020); Cahn (2020); Council and Uberti (2020); DeAngelis (2020); George et al. (2020); Kilpatrick and Barter (2020); Kumar et al. (2020); Laluyaux (2020); Lin and Lanng (2020); Queiroz et al. (2020); Raghu (2020); Sharma A et al. (2020a, 2020b); Zhu et al. (2020)
Digital Supply Networks	• A digital twin of the entire supply chain • Digital twins of warehouses	Risk management Collaboration Visibility	Some disruptions can be avoided by the integration of all supply chain members in a model of the supply chain. This facilitated collaboration and increased visibility that can enable better avoidance of pandemic caused disruptions and improved responses to them once they have occurred	Agrawal et al. (2020); Cahn (2020); Hassoun and Mawet (2020); Ivanov (2020); Kilpatrick and Barter (2020); Kumar et al. (2020); Queiroz et al. (2020); Zhu et al. (2020); Sharma et al. (2020a)