Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing

Abstract

The Industry 4.0 (I4.0) revolution has led to rapid digital transformation, automation of manufacturing processes and efficient decision-making in business operations. Despite the potential benefits of I4.0 technologies in operations management reported in the extant literature, there has been a paucity of empirical research examining the intention to adopt I4.0 technologies for managing risks. Risk management identifies, assesses, and introduces responses for risks to avert crises. This study combines institutional theory, the resource-based view and the technology acceptance model to develop a novel behavioural model examining the adoption of big data, artificial intelligence, cloud computing, and blockchain for risk management from the operations manager's perspective, which has never been examined in the literature. The model was tested for each I4.0 technology using data collected from 117 operations managers in the UK manufacturing industry which were analysed using structural equation modelling. We contribute to the theory on I4.0 in digital manufacturing by showing the impact of digital transformation maturity, market pressure, regulations, and resilience on the perceived usefulness and adoption of these technologies for managing risks in business operations. Based on the findings, we discuss implications for operations managers effectively and efficiently to adopt I4.0 technologies aiming to boost operational productivity.

Publication DOI: https://doi.org/10.1016/j.techfore.2022.121562
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Aston University (General)
Funding Information: This research was supported by the Productivity Insights Network grant number ES/R007810/1 from the Economic and Social Research Council and the Aston Seed Corn Grant.
Additional Information: © 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license 4.0 Funding: This research was supported by the Productivity Insights Network grant number ES/R007810/1 from the Economic and Social Research Council and the Aston Seed Corn Grant.
Uncontrolled Keywords: Digital manufacturing,Emergent technologies,Industry 4.0,Risk management,Structural equation modelling,Business and International Management,Applied Psychology,Management of Technology and Innovation
Publication ISSN: 1873-5509
Last Modified: 06 Dec 2024 08:27
Date Deposited: 17 Feb 2022 17:30
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 0944?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2022-05
Published Online Date: 2022-02-14
Accepted Date: 2022-02-05
Authors: Rodríguez-Espíndola, Oscar (ORCID Profile 0000-0002-4889-1565)
Chowdhury, Soumyadeb (ORCID Profile 0000-0002-8074-248X)
Dey, Prasanta Kumar (ORCID Profile 0000-0002-9984-5374)
Albores, Pavel (ORCID Profile 0000-0001-7509-9381)
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)

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