University of Tehran Press Industrial Management Journal 3115-7386 18 4 2026 10 01 Managing Agility and Efficiency under Uncertainty in Supply Chains: A Dynamic Capabilities Framework Based on Fuzzy Cognitive Maps 205 234 108645 10.22059/imj.2026.417468.1008328 EN Mohammad Reza Sadeghi Moghadam Associate Prof., Faculty of Industrial and Technology Management, College of Management, University of Tehran, Tehran, Iran. 0000-0002-9584-581X Taha Mansouri Associate Prof., School of Science, Engineering & Environment, the University of Salford, Salford, Greater Manchester, UK. 0000-0003-1539-5546 Amirhosein Mardani Ph.D., Faculty of Economics and Management, Tarbiat Modares University, Tehran, Iran. 0000-0003-2694-7457 Mahdi Azzavi MSc., Department of Performance Management, Faculty of Economic and Management, University of Qom, Qom, Iran. 0000-0002-4573-1486 Journal Article 2026 06 28 Objective: Information and Communication Technology (ICT) companies operate in highly dynamic environments characterized by rapid technological change and substantial uncertainty. Although organizational agility is widely recognized as an effective response to uncertainty, achieving agility often requires sacrificing efficiency, creating an enduring agility–efficiency tradeoff. This study aims to develop a quantitative framework for analyzing this tradeoff from a dynamic capabilities perspective. Methodology: A fuzzy cognitive map (FCM) approach was employed to model the causal relationships among dynamic capabilities, organizational agility, and efficiency. Research variables were identified through a comprehensive literature review and refined through expert panels. The FCM was developed based on the judgments of 30 experts from 12 leading Iranian ICT companies, including chief executive officers, marketing managers, technical managers, and senior strategy specialists. Results: The findings indicate that dynamic capabilities play unequal roles in managing the agility–efficiency tradeoff. Sensing, seizing, and transformation capabilities exert different levels of influence on organizational agility and efficiency. The simulation results further show that alternative capability development strategies lead to different organizational outcomes under conditions of uncertainty. Conclusion: The proposed FCM-based framework provides a quantitative decision-support tool for understanding and managing the agility–efficiency tradeoff in uncertainty-driven industries. The study contributes to the dynamic capabilities literature by integrating uncertainty management, organizational agility, and efficiency within a unified analytical framework. https://imj.ut.ac.ir/article_108645_82261c4d50a370d548ed49b8d4c8cc95.pdf