A model of structured decision making for the implementation of digital technologies in the logistics sector to achieve a competitive advantage

Abstract

Purpose . This paper investigates how strategic decision-making; structured project management methodologies and technology complexity jointly influence competitive advantage in the logistics sector. Design/methodology/approach . Data were collected through a bilingual (English.Lithuanian) expert survey of 60 logistics professionals involved in technology implementation projects. The study reports bivariate correlations and estimates separate ordinal logistic regression models to test five theory-derived hypotheses grounded in the resource-based view (RBV) and the dynamic capabilities perspective; an additional reverse competitive advantage and strategic goals (CA Ø SG) specification is reported only as a supplementary exploratory feedback analysis. Findings . The results indicate positive associations between (1) decision-making quality and competitive advantage, (2) strategic goal alignment and competitive advantage, (3) project management methodology and decision-making quality, (4) implementation speed and project management methodology, and (5) strategic decision-making quality and greater consideration of technology complexity. Across surveyed firms, digital technologies appear to be used primarily to support cost-based competitive advantage, while differentiationoriented benefits are rated lower. Given the cross-sectional design, findings are interpreted as evidence of association rather than definitive causal confirmation. Research limitations/implications . Future research should test the model across diverse regions, industries, and technological contexts to enhance generalizability and uncover additional moderating factors influencing competitive advantage. Practical implications . Practically, it provides guidance for phased digital transformation in logistics, emphasizing the need for structured decision-making, strategic alignment, and project management to navigate complex technologies. Social implications . The study showed that effective strategic decision-making increases competitive advantage, especially when it is aligned with clearly defined strategic goals and structured project management practices. The complexity of technology influences decision-making and project implementation, so adaptive, data-driven approaches are needed for successful digital technology adoption. Originality/value . This study empirically tests an integrated, theory-derived (RBV/dynamic capabilities) capability-to-outcome framework for digital technology implementation in logistics. Based on the empirical estimates, the framework offers scholars and practitioners a structured basis for planning phased digital transformation, aligning technology portfolios with strategic objectives, and managing risks in complex logistics initiatives.