Corporations are leveraging machine learning (ML) to create business value (BV). So, it becomes relevant to not only ponder the antecedents that influence the ML BV process but also, the main actors that influence the creation of such value within organizations: data scientists and managers. Grounded in the dynamic-capabilities theory, a model is proposed and tested with 319 responses to a survey. While for both groups, platform maturity and data quality are equally important factors for financial performance, information intensity is an equally important factor for organizational performance. On one hand, data scientists care more about the catalytic effect of data quality on the relationship between platform maturity and financial performance, and the compatibility factor for organizational performance. On the other hand, managers care more about the feasibility factor for financial performance. The findings presented here offer insights on how data scientists and managers perceive the ML BV creation process.
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