Strategic Cost Management Practices and Competitive Advantage Achievement (gjstudies, 2016)
This research investigates the novel application of computational complexitytheory and algorithmic game theory to the domain of strategic cost management(SCM), proposing a paradigm shift from traditional accounting-based frameworksto a dynamic, multi-agent systems approach. While conventional SCM literaturefocuses on cost reduction and value chain analysis, this paper introduces the concept of ’Algorithmic Cost Ecosystems’ (ACEs), where cost structures are modeledas evolving computational entities within a competitive landscape. The central research question explores how firms can achieve sustainable competitive advantageby treating cost management not as a static optimization problem, but as a continuous, strategic game against competitors, suppliers, customers, and internal processconstraints. The methodology employs agent-based modeling and simulation, constructing a virtual market with heterogeneous firms implementing different coststrategies derived from computational principles such as heuristic search, swarmintelligence, and regret minimization. Key findings demonstrate that strategiesmimicking approximation algorithms for NP-hard problems outperform traditionalvariance analysis and activity-based costing in volatile environments. Specifically,firms employing ’metaheuristic cost adaptation’—continuously generating and testing cost configuration hypotheses—achieved 23% higher resilience to supply chainshocks and 18% greater long-term profitability in simulated markets over a 10-yearperiod. The paper concludes that competitive advantage in cost management isless about pinpoint accuracy in cost allocation and more about the speed and intelligence of a firm’s adaptive response to cost structure perturbations, a capabilitywe term ’computational cost agility.’ This represents a significant departure fromestablished SCM theory, suggesting future integration with machine learning anddistributed ledger technologies for autonomous cost strategy evolution.