Big data analytics (BDA) is accepted to be an important driver of business value. Deriving value from big data to improve organizational decision-making requires the collaboration of data science experts and business users. However, recent literature has shown that their relationship is troubled. Tension arises from diverse relational difficulties and change-inherent challenges. The relationship has been theorized to lack social capital, which leads to inferior collaboration and diminishes project success. In this vein, scholars have begun to investigate relational governance mechanisms, but detailed insights on collaborative approaches to foster the relationship remain scarce. By applying multiple-case research, we shed light on collaborative mechanisms and reveal their impact on the relationship between data science and business employees, theorized by means of social capital. Thus, we build theoretical and practical bridges over the troubled waters in BDA collaboration and contribute to BDA success from a social perspective.
Hagen, Janine; Pély, Jacqueline-Amadea; and Hess, Thomas, "Collaborative mechanisms for big data analytics projects: Building bridges over troubled waters" (2022). ECIS 2022 Research Papers. 19.
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