Beyond Big Data: How Business Intelligence and Ambidexterity Drive Sustainable Telecom Performance

Objectives: This study examines how big data analytics capability (BDAC), organizational culture (OC), and decision-making capability (DMC) shape organizational ambidexterity (OA) in telecommunications firms, both directly and through business intelligence (BI) as a mediator, and how ambidexterity drives company efficiency and performance (CEP) and, in turn, environmental performance (EP). Methods/Analysis: A structured online survey of 199 telecom professionals measured seven reflective constructs (36 items), and the integrated model was tested using partial least squares structural equation modeling (PLS-SEM) with 5,000 bootstrap resamples. Findings: Six of nine hypotheses were supported. Decision-making capability was the strongest driver of ambidexterity; business intelligence fully mediated big data analytics capability and partially mediated decision-making capability; organizational culture showed no significant effect. Ambidexterity predicted company efficiency (β = 0.76), which improved environmental performance (β = 0.60), explaining about 60% of ambidexterity’s variance. Novelty/Improvement: The study contributes an integrated model linking data capabilities, business intelligence, and ambidexterity to environmental performance in telecom, among the first to extend the ambidexterity-performance link to an environmental outcome through the natural resource-based view, with the Baldrige Excellence Framework as an organizing lens. It advances fragmented accounts by showing that business intelligence and decision-making, not raw data or culture, drive sustainable performance.