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Abstract To examine the productivity paradox in the digital era, we explore the impact of digital transformation (DT) on total factor productivity (TFP). Based on a large sample of Chinese manufacturing firms, this study conducts a machine learning approach to examine the effects of DT on TFP at the strategy, technology, and application levels. The results indicate that blockchain, DT strategy, cloud computing, artificial intelligence, DT application, and big data, in ascending order of importance, positively affect TFP. Overall, this study enriches DT literature by verifying the impact of DT indexes on TFP and helps companies make decisions when undertaking DT implementation.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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