Big data analytics capabilities and knowledge management: impact on firm performance

TLDR

Big data analytics transforms raw data into actionable knowledge that can enhance decision‑making and firm performance, yet the integration of this knowledge with existing firm knowledge remains largely unexplored. The paper investigates how knowledge‑management practices mediate the relationship between BDA capabilities and firm performance. Using structural equation modeling on data from 88 Italian SMEs, the authors examined the direct impact of BDA capabilities on performance and the mediating role of knowledge management. The study finds that firms with stronger BDA capabilities—both technological and managerial—achieve higher performance, and that a knowledge‑management orientation significantly amplifies this effect, underscoring BDA’s potential to reshape competitive advantage.

Abstract

Purpose Big data analytics (BDA) guarantees that data may be analysed and categorised into useful information for businesses and transformed into big data related-knowledge and efficient decision-making processes, thereby improving performance. However, the management of the knowledge generated from the BDA as well as its integration and combination with firm knowledge have scarcely been investigated, despite an emergent need of a structured and integrated approach. The paper aims to discuss these issues. Design/methodology/approach Through an empirical analysis based on structural equation modelling with data collected from 88 Italian SMEs, the authors tested if BDA capabilities have a positive impact on firm performances, as well as the mediator effect of knowledge management (KM) on this relationship. Findings The findings of this paper show that firms that developed more BDA capabilities than others, both technological and managerial, increased their performances and that KM orientation plays a significant role in amplifying the effect of BDA capabilities. Originality/value BDA has the potential to change the way firms compete through better understanding, processing, and exploiting of huge amounts of data coming from different internal and external sources and processes. Some managerial and theoretical implications are proposed and discussed in light of the emergence of this new phenomenon.