The Impact of Big Data Analytics on Sustainable Firm Performance in the Telecommunications Sector in Libya: The Mediating Roles of Organizational Learning and Process-Oriented Dynamic Capabilities

Big data analytics (BDA) has emerged as a crucial strategic asset for organizations aiming to enhance their sustainable company performance; nevertheless, empirical information elucidating the correlation between analytics and sustainability results is scarce, especially in developing nations. This study examines the influence of big data analytics (BDA) on sustainable firm performance (SFP) within the Libyan telecommunications sector, focusing on the mediating roles of organizational learning (OL) and process-oriented dynamic capabilities (PODCs), utilizing dynamic capability and organizational learning theories. A quantitative, cross-sectional research design was utilized. A systematic questionnaire was used to collect data from personnel at five different managerial and functional levels in the Libyan telecoms sector. There were 354 valid replies from a group of 5400 professionals who worked in the managerial, technical, and strategic areas. We used Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS 4.0 to look at the proposed research model. We used measurement scales from previous investigations. The findings demonstrate that BDA exerts a positive and statistically significant influence on SFP. Nonetheless, this direct effect is quite minor when juxtaposed with the indirect effects conveyed by OL and PODCs. Both organizational learning and process-oriented dynamic capabilities significantly and partially mediate the relationship between big data analytics (BDA) and sustainable performance. This shows that analytics-driven sustainability outcomes depend heavily on a company’s ability to learn from data and change how it does things. This study enhances the Business and Management literature by elucidating the inadequacy of analytics investments in producing robust sustainability outcomes. It emphasizes the essential function of supplementary organizational capabilities in converting data-driven insights into enduring economic, environmental, and social value. From a practical standpoint, the findings indicate that managers and policymakers in developing economies ought to prioritize learning systems and adaptive process capabilities in conjunction with digital investments to fully harness the sustainability potential of big data analytics.