Exploring pathways to digital transformation: fsQCA analysis based on the AMO framework

Jun Liu, Ziwei Wang, Changjin Li and Ruofan Xu

PLOS ONE, 2024, vol. 19, issue 12, 1-18

Abstract: In recent years, China has significantly increased its global competitiveness in digital technologies, emphasizing the importance of the digital economy during the high-quality development stage. The question of how firms in traditional industries can achieve digital transformation, which is critical for participating in the digital economy, is still understudied. Using the ability-motivation-opportunity (AMO) framework, this research developed a model and identified six factors’ ability, motivation, and opportunity dimensions. It used fuzzy-set qualitative comparative analysis (fsQCA) to investigate their synergistic effect on digital transformation. With manufacturing firms in China as examples, the findings were as follows. First, no single factor could provide the necessary conditions for digital transformation, implying that the synergistic effect of multiple conditions must be considered. Second, four configurations with three paths for high digital transformation, namely motivation-opportunity-oriented, total factor-oriented, and motivation-oriented, showed different approaches to digital transformation under different conditions. These findings shed light on the complex causal relationships among antecedents of digital transformation and provide theoretical and practical recommendations for businesses looking to implement the digital process.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0315249

DOI: 10.1371/journal.pone.0315249

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