A dynamic capability perspective on the impact of big data analytics and enterprise architecture on innovation: an empirical study

Abstract

Purpose

The prevailing conceptualization of information system (IS) capabilities, rooted in the resource-based view (RBV) framework, tends to focus on unique firm resources. In the digital age, as emphasized by dynamic capabilities (DC), resource reconfiguration is critical in maintaining strategic advantage. This paper focuses on big data analytics capabilities (BDAC) from a DC perspective to present a novel conceptualization of BDAC–DC. We examine its effects on product, business model and business process innovation, including the effects of enterprise architecture (EA) on the BDAC business model innovation relationship.

Design/methodology/approach

This research presents a novel DC-based BDAC conceptualization, operationalized as a hierarchical construct. A survey-based approach is used for data collection and data analysis is done using partial least squares structural equation modeling (PLS-SEM).

Findings

The novel conceptualization and the effects of BDAC DC on BDA sensing-seizing and reconfiguration capacities support BDAC’s functional and evolutionary roleplay. Empirical results confirm the positive effects of BDAC–DC on first-order value targets (innovation) and the moderating effects of EA.

Research limitations/implications

The novel BDAC–DC conceptualization has several implications for BDAC, DC, EA and business value research. Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation.

Practical implications

Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation for synergistic outcomes.

Originality/value

To the best of our knowledge, this research is the first attempt toward DC-based BDAC conceptualization, empirical validation of first-order effects on various forms of innovation and the often-overlooked role of critical EA capability.