## 2 Materials and Methods
### Using the TOPSIS Method to Evaluate the Competitiveness of French-Speaking African Countries  
The TOPSIS method is a multi-index evaluation and decision-making method, first proposed by [PERSON] and [PERSON] in 1981. It is also known as the superiority-inferiority distance method. It is mainly used to evaluate the relative superiority of existing objects [33]. In recent years, it has been widely used in the comprehensive benefit evaluation of land use [34], comparative evaluation of tourism resources [35], comparative evaluation of urban economy [36], and other studies. However, few domestic and foreign scholars have touched on the quantitative evaluation of the competitiveness of cross-regional countries from a political and geographical perspective. This study chose the TOPSIS method based on its unique adaptability to the characteristics of African French-speaking countries and research objectives, which is specifically reflected in the three dimensions of data applicability, methodological characteristics, and regional research applicability. First, in terms of data applicability, African French-speaking countries face prominent challenges such as incomplete statistical data and severe heterogeneity. The TOPSIS method shows strong robustness to some data gaps: its core logic is to calculate the relative distance between the evaluation object and the \"ideal/negative ideal solution\" [33], and the normalization process can effectively weaken the impact of missing values within a certain range. In contrast, modern multi-criteria decision models (MCDMs) such as SPOTIS and ESP-COMET have stricter requirements on data integrity--SPOTIS relies on the precise determination of \"indifference thresholds\" and \"preference thresholds\", while ESP-COMET requires complete fuzzy preference information, which is difficult to meet in the context of data scarcity in Africa [37]. Second, in terms of methodological characteristics, this study focuses on a static cross-sectional competitiveness assessment of 26 countries, which requires a method that can accurately reflect relative advantages and disadvantages. The TOPSIS method directly quantifies the gap between countries and the optimal benchmark through Euclidean distance, and its results are intuitive and easy to understand, which is crucial for subsequent spatial pattern analysis [38]. Although the temporal MCDA technique is suitable for dynamically tracking time series changes, it is not necessary for the cross-sectional comparison of this study; its complex time weighting mechanism may even introduce redundant information. Third, in terms of the applicability of regional studies, the TOPSIS method has been widely verified in similar multi-indicator evaluation scenarios, such as comprehensive land use benefit evaluation [34], comparative evaluation of tourism resources [35], and urban economic evaluation [36]. These studies have confirmed its effectiveness in dealing with multi-dimensional and multi-scale evaluation objects, providing a methodological basis for cross-national competitiveness analysis. In contrast, newer methods such as SPOTIS lack sufficient application cases in African economic research, making it difficult to ensure the comparability of the results with the existing literature. The TOPSIS method constructs the \"ideal solution\" and \"negative ideal solution\" of each indicator in the indicator system, analyzes and compares the distance of each research object from the \"ideal solution\" and the \"negative ideal solution\", and gives the ranking of the comparison objects as the basis for decision-making [38]. The \"ideal solution\" meansthat each indicator is assumed to be optimal, while the \"negative ideal solution\" assumes that each indicator is the worst. In order to reflect the differences between indicators, different weights are usually given to each indicator.