Title: Driving factors of digital transformation for manufacturing enterprises: a multi-case study from China

Authors: Yanyu Wang; Xin Su

Addresses: School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China ' School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Abstract: With diminishing low-cost advantages, the Chinese manufacturing industry is actively engaged in digital transformation under the pressure of global competition. By analysing the gaps between existing technology-adoption theories and digital transformation practices, we developed a theoretical framework of factors influencing artificial intelligence (AI) adoption in enterprises based on the technology-organisation-environment (TOE) framework. Using three case studies of Chinese heavy-manufacturing enterprises, this article explores three important aspects of digital transformation empowered by AI: technological, organisational, and environmental driving factors and we propose an AI business model to clarify the mechanism of AI technological adoption in the manufacturing industry. This study is an in-depth summary and exploration of the digital transformation of China's manufacturing industry. It theoretically supplements related research in the field of AI technology adoption, and more important, provides practical experience in moving toward a digital transformation and upgrading of the manufacturing industry.

Keywords: digital transformation; manufacturing industry; artificial intelligence; China; driving factors; case study; technology adoption; technology-organisation-environment; TOE framework.

DOI: 10.1504/IJTM.2021.120932

International Journal of Technology Management, 2021 Vol.87 No.2/3/4, pp.229 - 253

Accepted: 08 Aug 2021
Published online: 17 Feb 2022 *

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