Integrating Transportation Engineering and Business Administration: Optimising Cost, Efficiency, and Service Delivery

Abstract

This study bridges the critical divide between transportation engineering and business administration by introducing the Strategic Transportation Optimisation Model (STOM)—a novel framework that dynamically aligns road network operations with strategic business objectives. Moving beyond siloed optimisation of traffic flows, signaling patterns, and journey times, STOM integrates customer satisfaction, logistics costs, and business profitability directly into the mathematical core of route planning. Using a digital twin of 1.8 million deliveries across North American and European freight networks, we demonstrate that STOM—powered by a regression-based feedback loop—adapts multi-objective vehicle routing in real time based on corporate strategy (Cost Leadership, Service Differentiation, Sustainability Commitment). The model simultaneously reduces total business costs by 9.1%, improves on-time in-full delivery (OTIF) by 9.9 percentage points, enhances customer lifetime value retention by 19.1%, and lowers average journey time by 16%, whilst increasing environmental performance (Green Impact Index, GII) by 25.5%. Unlike static models that treat traffic signals, road network constraints, or travel time as technical limits, STOM treats them as strategic levers influenced by customer satisfaction and operational cost trade-offs. Results confirm that when logistics decisions are engineered to reflect not just efficiency but economic and experiential outcomes, sub-optimisation is replaced by synergistic performance. STOM transforms the transport network from a passive infrastructure into an adaptive, value-generating system where traffic flows, journey times, and business costs are co-optimised for strategic alignment. The study demonstrates the viability of strategic-logistics integration, with implications moderated by organizational digital maturity.