Title: Factor conditions and capability building of artificial intelligence empowered digital transformation in the banking sector: a case study of a Chinese bank
Authors: Xin Su; Yanyu Wang
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: Digital capabilities and financial technologies have gained increasing attention in recent years. However, the factor conditions and capability building are not clarified and there is no comprehensive competency model to summarise the theoretical findings and industrial practices. Herein, an in-depth single case study of the largest state-owned commercial bank in China was conducted to explore factor conditions and capability building of digital transformation in the banking sector using interviews and questionnaires. The findings identified three driving factors and four restraining factors of digital transformation, and a synergy-technology-agility-resource (STAR) business model was proposed subsequently to match these factor conditions. Furthermore, a fuzzy-set qualitative comparative analysis (fsQCA) approach was adopted to analyse factor configurations and further demonstrate the qualitative results. This study contributed to the field by summarising the factor conditions and business capabilities of artificial intelligence (AI) applications in the banking industry, categorising the digital transformation processes into several configuration solutions, and providing a theoretical framework and practical guidance for academia and industry.
Keywords: artificial intelligence; AI; digital transformation; banking industry; factor conditions; business capabilities; fsQCA approach.
International Journal of Technology Management, 2025 Vol.97 No.2/3, pp.162 - 194
Received: 04 Oct 2022
Accepted: 07 May 2023
Published online: 02 Jan 2025 *