Pathway to Smart Aviation: Identifying and Prioritizing Key Factors for Smart Aviation Development Using the Fuzzy Best–Worst Method

Smart aviation has received significant attention from various stakeholders in China as its advancement holds crucial implications for the aviation industry, and there is a growing need for aviation authorities to assess the extent of its development. The evaluation of smart aviation development processes rely on various factors that reflect the smart aviation development level, and these factors could help pave the way for the successful development of smart aviation. However, few studies have focused on the identification and prioritization of the key factors for smart aviation development, especially considering the uncertain nature of the problem. To this end, this study employs the grounded theory and the fuzzy best–worst method (BWM) to identify and prioritize the factors for smart aviation development. Through the utilization of grounded theory, 37 factors are determined to be critical for smart aviation development. Then, the fuzzy BWM is employed to evaluate and prioritize the identified factors considering their importance. The findings of this study reveal that the 4D track development level, proportion of R&D investment, and data resources sharing degree are the most influential factors for smart aviation development. By integrating grounded theory, fuzzy sets, and BWM, this study identifies and prioritizes the significant factors for smart aviation for the first time. In general, the outcomes of this study hold the potential to guide practitioners in focusing on the pivotal factors that contribute to smart aviation development.