What determines the performance of digital transformation in manufacturing enterprises? A study on the linkage effects based on fs/QCA method

• Published in: Journal of cleaner production 2024-04, Vol.450, p.141856, Article 141856
• Main Authors: Shang, Meng, Jia, Chunjie, Zhong, LingLing, Cao, Junwei
• Format: Article
• Language: English
• Subjects: Digital transformation; Fs/QCA; TOE framework
• ISSN: 0959-6526
• DOI: 10.1016/j.jclepro.2024.141856

The achievement of high-quality development in the manufacturing industry can be effectively realized through the process of digital transformation. The enhancement of digital transformation performance in manufacturing enterprises has emerged as a prominent topic of interest for both corporate entities and the academic community. Drawing upon the theoretical framework of the TOE model, this article presents a comprehensive analytical framework aimed at understanding the performance of digital transformation in manufacturing enterprises. By assessing a sample of 180 manufacturing enterprises currently undergoing digital transformation, this study employs the fuzzy-set qualitative comparative analysis (fs/QCA) methodology to study the interrelated effects and strategic choices pertaining to technology, organizational structure, and environmental conditions, all of which contribute to the improvement of digital transformation performance in manufacturing enterprises. The findings of the research indicate the following: (1) The attainment of high performance in digital transformation in manufacturing enterprises does not solely rely on a single condition, whether it pertains to the optimization of manufacturing processes or the development of new products. (2) High performance in digital transformation is the result of multiple interacting factors. Various causal configurations, such as “organization-environment oriented”, “all-factor driven”, and “technology-environment oriented”, which have the characteristics of “multiple concurrency” and “different paths leading to the same goal.” (3) In comparison, achieving high performance in manufacturing process optimization requires a higher degree of complexity than attaining high performance in new product development. Additionally, it is challenging to achieve high performance in new product development with a sole reliance on a single technological foundation and external environmental support. These research conclusions contribute to the existing body of knowledge on digital transformation performance, enhancing our understanding of the complex factors that underlie high performance in digital transformation in manufacturing enterprises. Importantly, they hold practical significance in improving the performance of digital transformation in the manufacturing sector.