Accounting Information Contribution to Supply Chain Cost Management

Abstract

This research introduces a novel methodological framework that integrates accounting information systems with supply chain cost management through a bioinspired optimization approach, diverging from traditional linear accounting models. We propose the Pheromone-Based Cost Allocation (PBCA) algorithm, which
mimics ant colony foraging behavior to dynamically allocate indirect costs across
complex, multi-tier supply networks. Unlike conventional activity-based costing,
PBCA treats cost pools as dynamic pheromone trails that evaporate and intensify
based on real-time transactional data, enabling adaptive cost tracing in volatile supply environments. Our methodology employs a cross-disciplinary synthesis of swarm
intelligence principles, managerial accounting theory, and supply chain analytics to
address the persistent challenge of opaque cost structures in extended enterprise
networks. Through simulation of a five-tier manufacturing supply chain with 127
nodes, we demonstrate that PBCA reduces cost allocation errors by 42% compared
to traditional methods and identifies previously hidden cost drivers in supplier relationships. The algorithm’s emergent property of cost trail optimization reveals
non-linear cost propagation patterns that challenge standard cost-volume-profit assumptions. This research contributes original insights into how bio-inspired computational models can transform static accounting data into dynamic decision-support
tools, offering supply chain managers a novel mechanism for cost transparency and
strategic alignment. Our findings suggest that accounting information systems,
when reconceptualized through biological metaphors, can evolve from retrospective
reporting instruments to proactive supply chain coordination mechanisms.