Operations and Supply Chain Management | 2026
Authors: Wang X.; Huang Q.; Ohmori S.; Hasuike T.
DOI: 10.31387/OSCM0650522
Journal: Operations and Supply Chain Management
Year: 2026
Publisher: Operations and Supply Chain Management Forum
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
This study proposes a novel network Data Envelopment Analysis (DEA) model to evaluate supply chain performance from both cost and revenue perspectives. Although DEA is a widely used method for evaluating the relative efficiency of decision-making units (DMUs) with multiple inputs and outputs, traditional DEA models encounter difficulties when applied to multi-stage systems involving intermediate products, such as supply chains. To overcome these challenges, we extend the well-established Range Adjusted Measure (RAM) to develop a customized network DEA model that effectively captures the internal structure of supply chains. Our model enables accurate efficiency evaluation across different production stages and offers valuable insights into inefficiency sources. A case example of global supply chain network is conducted, incorporating data from suppliers, factories, sales distributors, and customers across multiple regions. We conducted five distinct evaluation scenarios that reflect various strategic objectives and supply configurations. Through these scenarios, we analyze the performance of diverse supply chain structures, identify inefficiency factors, and explore decision-making strategies such as suggested sourcing of parts factories and selection of parts and assy factories. Furthermore, we compare the consistency and difference between the overall and the stage-level scores in each scenario, thereby demonstrating the necessity and effectiveness of our proposed model for evaluating supply chain efficiency. Consequently, the results indicate that the model not only evaluates performance but also supports strategic supply chain design and improvement. © (2026), (Operations and Supply Chain Management Forum). All rights reserved.
cost and revenue efficiency; data envelopment analysis; network structure; range adjusted measure; supply chain performance