Enhancing innovativeness and performance of the manufacturing supply chain through datafication: the role of resilience

Tian, Shuang; Wu, Lin; Pia Ciano, Maria; Ardolino, Marco; Pawar, Kulwant S.

Abstract

The Covid-19 pandemic has extremely affected the manufacturing supply chain (SC) highlighting the need to deploy dynamic capabilities (DCs) such as supply chain resilience (SCRes) that enable companies to react rapidly and exploit intangible assets to support long-term performance. Concurrent with the needs dictated by the pandemic, companies are faced with rapid technological development driven by Industry 4.0. Massive amounts of information lead to the need for effective 'datafication', where information is standardized and recorded through technologies such as the Internet-of-Things (IoT), and processed by others like Artificial Intelligence (AI). In the disruptive context, companies can remain competitive by turning the crisis into an opportunity for innovation and improving their performance. This study thus explores the impact of datafication, represented by IoT and AI implementation, on manufacturing SC performance and innovativeness and investigates the role of SCRes. Analyzing data collected from 311 Chinese manufacturing companies reveals that datafication positively influences supply chain innovativeness and performance, in which SCRes plays a mediating role. The finding contributes to the ongoing debate on how digital technologies can help organizations improve DCs and achieve competitive advantage. This research also encourages companies, particularly those in developing countries, to take full advantage of Industry 4.0 technologies.

Citation

Tian, S., Wu, L., Pia Ciano, M., Ardolino, M., & Pawar, K. S. (2024). Enhancing innovativeness and performance of the manufacturing supply chain through datafication: the role of resilience. Computers and Industrial Engineering, 188, Article 109841. https://doi.org/10.1016/j.cie.2023.109841

• Journal Article Type: Article
• Acceptance Date: Dec 12, 2023
• Online Publication Date: Dec 15, 2023
• Publication Date: 2024-02
• Deposit Date: Dec 18, 2023
• Publicly Available Date: Dec 16, 2026
• Journal: Computers and Industrial Engineering
• Print ISSN: 0360-8352
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 188
• Article Number: 109841
• DOI: https://doi.org/10.1016/j.cie.2023.109841
• Keywords: Dynamic capabilities; Supply chain management; Supply chain resilience; Artificial intelligence (AI); Internet-of-things (IoT)
• Public URL: https://nottingham-repository.worktribe.com/output/28705374
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0360835223008653