Impact of digital technologies on manufacturing firm resilience during COVID-19 pandemic: a PLS-SEM and artificial neural network analysis

Abstract

Purpose The emergence of the COVID-19 epidemic has considerably increased the intricacy of information, exacerbating the difficulties firms encounter in efficiently processing and understanding accurate data and knowledge. Consequently, the COVID-19 epidemic has profoundly exacerbated production ambiguity for firms, thereby disrupting their regular business operations and supply chain activities. Digital technologies (DTs) are essential tools for firms to process and interpret information and knowledge, thereby improving their resilience against supply chain interruptions. Design/methodology/approach This research investigates the effect of digital technologies on firm resilience throughout COVID-19, utilizing PLS-SEM and artificial neural networks (ANN) derived from a comprehensive survey of Pakistani manufacturing firms. Findings Our research assesses the mediating role of supply chain integration, memory, and absorptive capacity, as well as the moderating influence of information complexity. The outcomes demonstrate that supply chain integration (SCI), memory (SCM), and absorptive capacity (SCAC) mediate digital technologies’ influence on firm resilience. Moreover, in situations where information is highly complex, DTs have a greater effect on a firm’s resilience. Originality/value The results enhance our comprehension and awareness of the resilience-related effects of DTs and offer significant management insights for strengthening firm resilience in the setting of the COVID-19 pandemic.

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