The role of artificial intelligence in effective business operations during COVID-19

Abstract

Purpose The pressure to survive in a highly competitive market by using artificial intelligence (AI) has further demonstrated the need for automation in business operations during a crisis, such as COVID-19. Prior research finds managers' mixed perceptions about the use of technology in business, which underscores the need to better understand their perceptions of adopting AI for automation in business operations during COVID-19. Based on social exchange theory, the authors investigated managers' perceptions of using AI in business for effective operations during the COVID-19 pandemic. Design/methodology/approach This study collected data through a survey conducted in China (N = 429) and ran structural equation modeling to examine the proposed research model and structural relationships using Smart PLS software. Findings The results show that using AI in supply chain management, inventory management, business models, and budgeting are positively associated with managers' satisfaction. Further, the relationship between managers' satisfaction and effective business operations was found to be positively significant. In addition, the findings suggest that top management support and the working environment have moderating effects on the relationship between managers' satisfaction and effective business operations. Practical implications The results of this study can guide firms to adopt an AI usage policy and execution strategy, according to managers' perceptions and psychological responses to AI. Social implications The study can be used to manage the behavior of managers within organizations. This will ultimately improve society's perception of the employment of AI in business operations. Originality/value The study's outcomes provide valuable insights into business management and information systems with AI application as a business response to any crisis in the future.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 51 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.