Big Data Analytics Capabilities, Strategic Agility, and Firm Performance: A Systematic Literature Review - Haryanto, Tri; Hurriyati, Ratih; Sultan, Mokh Adib (Riviera Publishing, 2026)
Background: In the era of digital transformation, Big Data Analytics Capabilities (BDAC) have emerged as critical drivers of firm performance. However, the mechanisms through which BDAC translates into sustainable competitive advantage particularly the mediating roles of strategic agility, entrepreneurial innovation, and organizational learning remain underexplored. Objective: This systematic literature review aims to synthesize and analyze the interrelationships among BDAC, strategic agility, entrepreneurial innovation, organizational learning, and firm performance within multinational corporations (MNCs), with a specific focus on emerging markets. Methods: Drawing on the Dynamic Capabilities View (DCV), this review follows PRISMA guidelines and synthesizes findings from 42 peer-reviewed articles published between 2019 and 2025, sourced from Scopus, Web of Science, and Google Scholar. A thematic analysis was conducted to identify key patterns, mediating mechanisms, and contextual factors. Results: The findings reveal that BDAC functions as a dynamic capability that enables sensing, seizing, and transforming processes. Strategic agility serves as both a direct and indirect driver of performance, mediated by entrepreneurial innovation and organizational learning. Contextual factors such as market dynamism, organizational culture, and digital infrastructure significantly moderate these relationships. The review identifies that BDAC-driven agility is particularly impactful in volatile emerging markets. Conclusion and Implications: This review contributes to theory by positioning BDAC as a strategic enabler within the DCV framework and clarifying the micro-foundations linking analytics to performance. Practically, it offers guidance for managers in emerging-market MNCs to cultivate data-driven, agile cultures and align analytics initiatives with strategic goals. Future research should employ longitudinal and cross-industry designs to strengthen causal inference and explore underexamined moderators