Data-Driven Decision-Making, Organisational Agility and Competitive Advantage of Telecommunication Firms in South Sudan
Keywords:
Data-driven decision making, Competitive advantage, Data access and utilisation, Data interpretation skills, Decision-making confidenceAbstract
The study examined the effect of data-driven decision-making and organisational agility on the competitive advantage of telecommunication firms in South Sudan. The study was based on positivist philosophy that informed the adoption of a cross-sectional research design. The target population constituted 11 active telecommunication firms that formed the unit of analysis. The study targeted 148 employees drawn from the board, executive, departments, middle management, and technical levels of each firm. Thereafter, a sample of 108 respondents was determined using Yamane’s 1967 formula before proportionate stratified sampling was adopted to ensure each staff category was represented in line with its population share. The achieved response rate was 92 (85.2%). Structured questionnaires were adopted in sourcing data before analysis was undertaken with the aid of the Statistical Package for Social Sciences. The regression analysis revealed that data-driven decision-making significantly affected the competitive advantage of telecommunication firms in South Sudan (β1 = 0.273, t = 3.285, p = .001). However, the effect of organisational agility on the competitive advantage of firms in the study was not significant (β2= -0.047, t = -0.665, p = .508). The study thus concluded that data-driven decision-making elements, including data access and utilisation, data interpretation skills, and decision-making confidence, were strongly and positively associated with competitive advantage of telecommunication firms in South Sudan. Consequently, the study recommends that managers and policymakers should prioritise initiatives aimed at strengthening data accessibility, analytics capabilities, and a culture of evidence-based decision-making. Future research should explore additional organisational and environmental factors that may influence the dependent variable.
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