Fuzzy Cognitive Map–Based Approach for Measuring Megaproject Complexity Considering Dynamic Interactions

As complex systems embedded in volatile social environments, megaprojects possess complexity, which is a systematic property that emerges from dynamic interactions among various complexity factors. Measurements of complexity that do not account for dynamic interactions can lead to a significant underestimation or misjudgment of the complexity challenges faced by megaproject delivery, resulting in inaccurate and incomplete measurement results. Given the limited managerial resources for megaprojects, quantifying the interactive effects and identifying the sensitive factors that have the greatest impact on complexity are critical for effectively governing complexity. However, existing research lacks robust measurement models capable of quantitatively measuring complexity considering dynamic interactions in megaprojects. Addressing this gap, this study proposes a novel measurement approach incorporating dynamic interactions to quantify how changes in individual factors influence overall megaproject complexity. Through semistructured interviews and the Delphi method, six influencing factors of megaproject complexity are identified: environmental (D1), institutional (D2), technological (D3), social (D4), task (D5), and organizational (D6). A fuzzy cognitive map (FCM) model, developed with expert input, captured these dynamic interactions. Predictive, diagnostic, and sensitivity analyses quantified variation magnitude, revealing technological (D3) and social complexity (D4) as the most influential factors. Validated via a real-world megaproject, the model enables project managers to quantitatively monitor complexity changes over time, supporting real-time dynamic analysis and proactive control.