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The global value chain describes the process of sourcing components from multiple countries and assembling them into final products elsewhere. Option A, vertical integration, refers to owning multiple stages of production internally. Option C and D describe more localized operations. In CSCP, the global value chain framework illustrates the interconnected nature of modern supply chains. For example, smartphones often source microchips from Taiwan, displays from South Korea, and assembly in China, before distributing globally. This model maximizes cost efficiency and leverages comparative advantages across countries but also introduces risks such as geopolitical instability and transportation complexity.

Economic Order Quantity (EOQ) is the order size that minimizes the combined costs of ordering and holding inventory. Option A emphasizes discounts, option C refers to buffers, and option D is unrelated. In CSCP, EOQ is introduced as a key inventory management model balancing cost and efficiency. For example, a manufacturer calculates EOQ to reduce the frequency of orders while avoiding excessive carrying costs, optimizing inventory investments.

A closed-loop supply chain integrates forward and reverse flows to maximize value recovery from returned products through reuse, recycling, and remanufacturing. Option A is tied to delivery efficiency, not closed-loop design. Option B is unrealistic, as safety stock is still required. Option D misrepresents the concept since logistics planning is critical in closed loops. In CSCP, closed-loop systems are discussed as essential for sustainability and competitiveness. For example, HP collects used ink cartridges, recycles plastic, and reintegrates materials into new products. This approach reduces waste, strengthens compliance with environmental regulations, and creates cost savings while enhancing brand image.

Nearshoring relocates production closer to end markets, reducing transportation lead times and improving responsiveness. Option A is typically achieved through offshoring, option C is unrealistic, and option D is unrelated. In CSCP, nearshoring is promoted as a strategy to balance efficiency with resilience. For example, U.S. firms nearshoring production to Mexico shorten delivery times, reduce risks from long supply chains, and increase agility in responding to customer demand.

Predictive maintenance leverages IoT sensors, machine learning, and analytics to predict equipment failures before they occur. Option A is preventive but not predictive, option B is reactive, and option D is a sourcing strategy. In CSCP, predictive maintenance is recognized as a transformative application of technology to reduce downtime, increase asset utilization, and lower maintenance costs. For example, logistics companies use IoT-enabled sensors on trucks to monitor engine health, predicting failures and scheduling maintenance proactively. This improves service reliability and reduces costly disruptions across the supply chain.