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This study proposes an innovative concept of green digital transformation capability (GDTC) and explores the interrelationships among GDTC, ambidextrous green learning (AGL) and sustainability performance (SP) from multiple perspectives.

Survey questionnaires were distributed to Taiwanese firms engaged in various sectors, including electrical and information, metal and precision machinery, rubber material, chemical, daily necessity and food and beverage manufacturing, resulting in 306 valid responses. Structural equation modeling in SPSS v26 was used to test the hypotheses. Furthermore, we analyzed the mediating effects using SPSS PROCESS.

The results demonstrated that GDTC affected SP both directly and indirectly through exploratory and exploitative green learning. Furthermore, this study revealed the pathways through which GDTC influenced the SP of Taiwanese manufacturing firms.

This study is limited to Taiwanese manufacturing firms. Future studies should expand their sample size to explore digital transformation (DT) practices in various regions and industries.

The DTs in manufacturing have profound social implications, emphasizing that companies should consider economic, social and environmental sustainability during digitalization.

This study introduces a novel concept of GDTC and provides important theoretical insights and practical implications for the intersection of DT and sustainability perspective. These findings will offer valuable guidance to companies seeking sustainable development in the digital era.