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

Year: 2025
Type: article
Study design: Observational Study
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.
DOI: 10.59075/jssa.v3i4.346
Language: English
Open Access status: hybrid
OpenAlex ID: W4414785573
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