Unleashing the power of big data for platform firms: A configuration analysis

Abstract

This study investigates the impact of big data on platform performance using a multidimensional perspective and the fuzzy set qualitative comparative analysis (fsQCA) method. We identify two pathways for platforms to leverage big data to achieve performance improvement: “volume-centric configuration” and “volume-talent synergistic configuration.” Our results indicate that big data volume and talent of big data are the core conditions impacting platform performance, but an increase in these factors does not always equate to an improvement in performance. The study makes two substantial contributions: (1) identifying the configurations of big data that lead to high performance of the platform and illuminating the complex interplay of causality between the multidimensional nature of big data resources and their supporting conditions and (2) measuring the multidimensionality of big data resources in platform firms through the utilization of operational data of the app in question. This study has significant practical implications, providing guidance to platform firms on identifying appropriate big data resources to gain a competitive advantage and utilizing supporting conditions to address deficiencies in data assets.