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The primary purpose of this study is to develop a novel framework to explain the effects of data-driven leadership in IR4.0 adoption on firm performance. We proposed four dimensions for the data-driven leadership: (1) the experience of key personnel with IR4.0 adoption, (2) the appointment of a chief information officer (CIO), (3) the establishment of a technology committee, and (4) the acquisition of technology. This study includes 943 public-listed firms traded on Bursa Malaysia from 2015 to 2019. Using the random effects model (REM), our study shows that data-driven leadership in IR4.0 adoption, particularly the appointment of a CIO and the acquisition of technology, is positively associated with Tobin’s [Formula: see text] and market-to-book value of the firms. Subsample analysis reveals that data-driven leadership has greater significant positive impacts on firm performance in manufacturing-related firms. Further analysis also provides evidence that CEO duality and CEO age negatively affect the role of CIO in manufacturing firms. In contrast, CEO age and founder CEO negatively affect the role of key personnel fitted with IR4.0 experience in nonmanufacturing firms. However, founder CEO in nonmanufacturing-related firms which incorporated IR4.0 technology into the business could significantly improve firm performance. Lastly, there is a noticeable drop in performance when the boards are busy. Our study provides recommendations to both industry and government IR4.0 policy and contributes to leadership literature scholarly, particularly in the data-driven leadership viewpoint in both manufacturing- and nonmanufacturing-related sectors in the era of IR4.0.
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