Explorative Learning as a Pathway Linking Big Data Analytics Enabled Dynamic Capabilities to Organizational Decision Making

Abstract

The recent Big Data Analytics (BDA) has also revolutionised the way organisations derive intelligence and react to environmental dynamics. The proposed study of this research suggests the design of a study by utilising the "Dynamic Capabilities" View and the Organisational Learning Theory as the means of identifying the interdependence between Big Data Analytics-enabled Dynamic Capabilities (BDAEDC) and Decision-Making Quality of Organisations (DMQO),through Explorative Learning (ELR). The survey was conducted using a structured questionnaire, which was administered to managers of various organisations. The proposed model was tested using “Partial Least Squares Structural Equation Modelling" (PLS-SEM). The results indicate that BDAEDC has a significant positive effect on decision quality and exploratory learning. Moreover, exploratory learning has a substantial influence on the quality of the decision-making process, which proves its significance in prompting necessary changes for organisations to adopt, innovate, and improve the quality of strategic decisions. The mediation analysis suggests a partial mediating effect of exploratory learning in the relationship between BDAEDC and DMQ, thereby reinforcing the idea that the value of data-enabling capabilities can be delivered not only directly but also indirectly, through facilitated learning within the organization. The article has helped provide a theoretical explanation of the interaction between dynamic capabilities, big data, and knowledge, while also offering practical advice to managers and coordinating the alignment of BDA initiatives and learning-based practices to enhance the quality of decision-making.