DEVELOPING COST-EFFICIENT, SUSTAINABLE LOGISTICS MODELS FOR U.S. MANUFACTURING INDUSTRIES

Povzetek

The contemporary manufacturing landscape in the United States is increasingly shaped by the dual imperatives of cost efficiency and environmental sustainability. As manufacturing firms confront rising operational expenses, fluctuating supply chain dynamics, and stringent regulatory requirements, the need for logistics models that simultaneously minimize costs and environmental impact has become critical. This research explores the development of integrated, cost-efficient, and sustainable logistics frameworks tailored specifically to U.S. manufacturing industries, with a focus on optimizing transportation, inventory management, and distribution strategies. The study employs a multi-dimensional approach, combining empirical data analysis, simulation modeling, and scenario-based evaluation to assess the performance of different logistics strategies. Key factors considered include fuel consumption, greenhouse gas emissions, warehouse operations, transportation routing, and procurement practices. By evaluating traditional logistics approaches alongside emerging sustainable practices such as route optimization technologies, consolidation of shipments, renewable energy utilization in warehouses, and adoption of green transportation vehicles, the study identifies opportunities for substantial cost savings without compromising operational effectiveness. Findings indicate that implementing an integrated logistics framework that aligns supply chain decisions with sustainability objectives can lead to significant reductions in both operational costs and environmental footprint. Specifically, strategic measures such as optimizing shipment schedules, leveraging advanced analytics for demand forecasting, and integrating multi-modal transportation systems were found to enhance efficiency while reducing carbon emissions. Moreover, the research highlights the importance of cross-functional coordination within manufacturing organizations, emphasizing that sustainability initiatives are most effective when logistics planning, procurement, and production operations are aligned. The study also presents a comparative analysis of cost implications associated with traditional versus sustainable logistics strategies, revealing that upfront investments in sustainable infrastructure and technology yield long-term financial and environmental benefits. In addition, sensitivity analyses demonstrate that cost savings and emission reductions are maximized when logistics decisions are informed by real-time data and predictive modeling, underscoring the value of adopting advanced information systems in manufacturing logistics. In conclusion, this research contributes to the literature on sustainable supply chain management by providing actionable insights and practical frameworks for U.S. manufacturing firms seeking to balance cost efficiency with environmental responsibility. The proposed logistics models serve as a roadmap for industry practitioners aiming to implement sustainable practices while maintaining competitive advantage, demonstrating that strategic integration of cost-efficient and eco-friendly logistics is not only feasible but also essential in the evolving industrial context.