OPTIMISING BIG DATA ANALYTICS AND KNOWLEDGE MANAGEMENT FOR SUSTAINABLE QUALITY MANAGEMENT IN UPSTREAM OIL & GAS PROJECTS: A QUANTITATIVE STUDY

Abstract

This research explores how big data analytics and knowledge management contribute to the development of quality management practices in the upstream oil and gas service industry, with the aim of strengthening operational efficiency and achieving sustainable project outcomes. A quantitative methodological approach is employed, concentrating on the relationship between knowledge management and quality management practices, as well as project sustainability performance, in addition to assessing the effect of big data analytic capability on quality management systems and project sustainability performance. The empirical data were obtained through purposive sampling of 183 senior professionals and managers working within project management offices. Data analysis was conducted using partial least squares structural equation modelling (PLS-SEM). The findings demonstrate that knowledge management has a strong and positive influence on both quality management practices and project sustainability performance. Conversely, big data analytic capability exhibits a relatively weaker effect, which is largely attributable to the early phase of digital technology adoption within the industry. Moreover, quality management practices are found to be a key determinant in enhancing overall project sustainability.