Evaluation of Competitiveness and Sustainable Development Prospects of French-Speaking African Countries Based on TOPSIS and Adaptive LASSO Algorithms
Abstract
1. Introduction
2. Materials and Methods
2.1. Overview of Study Area
2.2. Data Sources
2.3. Using the TOPSIS Method to Evaluate the Competitiveness of French-Speaking African Countries
Basic Steps of TOPSIS Method
2.4. Construction of Indicator System
2.5. Evaluation of Factors Affecting Competitiveness of French-Speaking African Countries Based on Adaptive LASSO Algorithm
3. Results
3.1. Competitiveness Evaluation Results of French-Speaking African Countries
3.2. Empirical Analysis of Factors Affecting Competitiveness of French-Speaking African Countries Based on Adaptive-LASSO Algorithm
4. Prospects and Strategies for Sustainable Development in French-Speaking African Countries
4.1. Sustainable Development Prospects
- Leverage effect of R&D investment: Currently, the proportion of R&D expenditure to GDP in French-speaking African countries is generally less than 1%. If referring to the global average of 2.5%, every 1 percentage point increase is expected to drive a 3–5% increase in the added value of high-tech industries.
- Structural opportunities for high-tech exports: High-tech exports in West Africa and Central Africa account for less than 5%, but high-tech exports of auto parts in Morocco in North Africa have achieved an annual growth of 12%, indicating that new growth poles can be formed through industrial upgrading.
- The risk resistance of financial reserves: Insufficient total reserves will lead to pressure on foreign debt repayment. If the ratio of total reserves to short-term foreign debt is increased to the 1:1 safety line, the risk of currency crisis can be reduced by 50%.
4.2. Targeted Strategies for Sustainable Development in French-Speaking African Countries: Synergistic Intervention Based on Key and Sub-Key Factors
- Strengthen scientific and technological R&D investment and innovation transformation mechanism.
- 2.
- Optimize financial reserve management and capital market vitality.
- 3.
- Strengthen the foundation of scientific and engineering talents and R&D manpower.
- 4.
- Increase the added value of commodity exports and facilitate trade.
- 5.
- Implementation path for China and Africa to jointly promote sustainable development.
5. Conclusions
5.1. Conclusions of This Study
5.2. Research Discussions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Competitiveness Range | Competitiveness Level |
---|---|
Low competitiveness | |
Low to medium competitiveness | |
Medium Competitiveness | |
Medium to high competitiveness | |
High competitiveness |
Overall Indicator | Primary Indicator | Secondary Indicator | Tertiary Indicator | Weight | Nature |
---|---|---|---|---|---|
Country Home Competition Fight Force N | Core Competitiveness A (0.6694) | Economic Level A1 | GDP X1/USD | 0.0542 | + |
Industrial added value X2/% | 0.0192 | + | |||
Value added of service industry X3/% | 0.0115 | + | |||
Goods export X4/USD | 0.0581 | + | |||
Technological Level A2 | Science and Engineering Indicators X5 | 0.0745 | + | ||
R&D expenditure as a percentage of GDP X6/% | 0.1472 | + | |||
R&D researchers X7/million people−1 | 0.0739 | + | |||
High-tech exports X8/USD | 0.1595 | + | |||
Patent application number X9/piece | 0.0926 | + | |||
Financial Strength A3 | Domestic listed companies X10/ | 0.0854 | + | ||
Total reserves X11/USD | 0.1160 | + | |||
Annual inflation rate X12/% | 0.0056 | − | |||
Total stock trading volume as a percentage of GDP X13/% | 0.1021 | + | |||
Basic Competitiveness B (0.2244) | Financial Strength B1 | Railway (total kilometers) X14/km | 0.1234 | + | |
Air transport volume X15/person | 0.1571 | + | |||
Container terminal throughput X16/ton | 0.1733 | + | |||
Power consumption X17/kWh·person−1 | 0.1631 | + | |||
Energy usage X18/kg oil·person−1 | 0.1271 | + | |||
Quality of Residents B2 | Total public expenditure on education as a percentage of GDP X19/% | 0.0497 | + | ||
Secondary school enrollment rate X20/% | 0.0587 | + | |||
University enrollment rate X21/% | 0.0992 | + | |||
Adult literacy rate X22/% | 0.0484 | + | |||
Auxiliary Competitiveness C (0.1062) | Government Role C1 | Government revenue as a percentage of GDP X23/% | 0.1309 | + | |
Government expenditure as a percentage of GDP X24/% | 0.0970 | + | |||
Central government debt as a percentage of GDP X25/% | 0.0671 | − | |||
Urbanization rate X26/% | 0.1013 | + | |||
Employment rate of population aged 15 and above X27/% | 0.1110 | + | |||
Living Environment C2 | GDP per capita X28/US dollar·person−1 | 0.3077 | + | ||
Health care expenditure as a percentage of GDP X29/% | 0.0964 | + | |||
Gini coefficient X30 | 0.0887 | − |
Core Competencies | Basic Competitiveness | Auxiliary Competitiveness | Comprehensive Competitiveness | Competitiveness Level |
---|---|---|---|---|
0.4661 ≤ A < 0.4768 | 0.4062 ≤ B < 0.4365 | 0.5315 ≤ C < 0.5396 | 0.4600 ≤ N < 0.4735 | Low competitiveness |
0.4768 ≤ A < 0.4876 | 0.4365 ≤ B < 0.4667 | 0.5396 ≤ C < 0.5477 | 0.4735 ≤ N < 0.4870 | Low to medium competitiveness |
0.4876 ≤ A < 0.4984 | 0.4667 ≤ B < 0.4969 | 0.5477 ≤ C < 0.5559 | 0.4870 ≤ N < 0.5005 | Medium Competitiveness |
0.4984 ≤ A < 0.5091 | 0.4969 ≤ B < 0.5272 | 0.5559 ≤ C < 0.5640 | 0.5005 ≤ N < 0.5140 | Medium to high competitiveness |
0.5091 ≤ A ≤ 0.5199 | 0.5272 ≤ B ≤ 0.5722 | 0.5640 ≤ C ≤ 0.5722 | 0.5140 ≤ N ≤ 0.5275 | High competitiveness |
Nation | Core Competencies | Basic Competitiveness | Auxiliary Competitiveness | Comprehensive Competitiveness |
---|---|---|---|---|
Algeria | 0.5185 | 0.5330 | 0.5320 | 0.5232 |
Benin | 0.4937 | 0.5376 | 0.5440 | 0.5089 |
Burkina Faso | 0.4938 | 0.5141 | 0.5370 | 0.5029 |
Burundi | 0.4884 | 0.5080 | 0.5315 | 0.4974 |
Equatorial Guinea | 0.4954 | 0.5245 | 0.5722 | 0.5101 |
Togo | 0.4910 | 0.5296 | 0.5449 | 0.5054 |
Congo (Brazzaville) | 0.5146 | 0.5295 | 0.5427 | 0.5209 |
Democratic Republic of the Congo | 0.4956 | 0.5315 | 0.5447 | 0.5088 |
Djibouti | 0.4947 | 0.5281 | 0.5451 | 0.5075 |
Guinea | 0.4917 | 0.5043 | 0.5370 | 0.4993 |
Gabon | 0.4956 | 0.5353 | 0.5466 | 0.5099 |
Cameroon | 0.4975 | 0.5373 | 0.5402 | 0.5110 |
Comoros | 0.4825 | 0.5115 | 0.5372 | 0.4948 |
Ivory Coast | 0.4975 | 0.5574 | 0.5451 | 0.5160 |
Rwanda | 0.4911 | 0.5098 | 0.5341 | 0.4999 |
Madagascar | 0.4929 | 0.5176 | 0.5318 | 0.5025 |
Mali | 0.4928 | 0.5109 | 0.5317 | 0.5010 |
Mauritius | 0.5080 | 0.5279 | 0.5685 | 0.5189 |
Mauritania | 0.4919 | 0.5162 | 0.5401 | 0.5025 |
Morocco | 0.5199 | 0.5405 | 0.5482 | 0.5275 |
Niger | 0.4909 | 0.4943 | 0.5335 | 0.4962 |
Senegal | 0.4984 | 0.5294 | 0.5457 | 0.5104 |
Seychelles | 0.5027 | 0.5227 | 0.5690 | 0.5142 |
Tunisia | 0.5165 | 0.5348 | 0.5420 | 0.5233 |
Chad | 0.5196 | 0.4213 | 0.5433 | 0.5000 |
Central Africa | 0.4661 | 0.4062 | 0.5356 | 0.4600 |
Variable Name | Correlation Coefficient | t Statistic | Relevance | p-Value |
---|---|---|---|---|
X_1 | 0.3821 | 3.52 | 0.856 | 0.001 |
X_2 | −0.2153 | −2.89 | −0.724 | 0.005 |
X_3 | 0.4572 | 4.11 | 0.892 | 0.000 |
X_4 | 0.2985 | 3.05 | 0.813 | 0.002 |
X_5 | −0.1867 | −2.23 | −0.688 | 0.028 |
X_6 | 0.5124 | 4.87 | 0.921 | 0.000 |
X_7 | 0.3546 | 3.33 | 0.837 | 0.001 |
X_8 | 0.4235 | 4.02 | 0.879 | 0.000 |
X_9 | 0.2654 | 2.78 | 0.795 | 0.006 |
X_{10} | 0.3178 | 3.19 | 0.825 | 0.003 |
X_{11} | 0.4891 | 4.66 | 0.905 | 0.000 |
X_{12} | −0.1235 | −1.67 | −0.542 | 0.098 |
X_{13} | 0.2843 | 2.91 | 0.802 | 0.004 |
Method | Number of Filter Variables | Core Factor Overlap Rate | BIC Value | Key Flaws |
---|---|---|---|---|
Adaptive-LASSO | 8 | 75% | 126.8 | - |
Traditional LASSO | 12 | 62.5% | 142.3 | Keep redundant variables |
Ridge regression | 30 | 50% | 189.5 | Unable to remove variables |
Random forest | 8 | 62.5% | 138.5 | Missing the key factor “R&D expenditure” |
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Liu, B.; Li, L.; Ren, H.; Qin, J.; Liu, W. Evaluation of Competitiveness and Sustainable Development Prospects of French-Speaking African Countries Based on TOPSIS and Adaptive LASSO Algorithms. Algorithms 2025, 18, 474. https://doi.org/10.3390/a18080474
Liu B, Li L, Ren H, Qin J, Liu W. Evaluation of Competitiveness and Sustainable Development Prospects of French-Speaking African Countries Based on TOPSIS and Adaptive LASSO Algorithms. Algorithms. 2025; 18(8):474. https://doi.org/10.3390/a18080474
Chicago/Turabian StyleLiu, Binglin, Liwen Li, Hang Ren, Jianwan Qin, and Weijiang Liu. 2025. "Evaluation of Competitiveness and Sustainable Development Prospects of French-Speaking African Countries Based on TOPSIS and Adaptive LASSO Algorithms" Algorithms 18, no. 8: 474. https://doi.org/10.3390/a18080474
APA StyleLiu, B., Li, L., Ren, H., Qin, J., & Liu, W. (2025). Evaluation of Competitiveness and Sustainable Development Prospects of French-Speaking African Countries Based on TOPSIS and Adaptive LASSO Algorithms. Algorithms, 18(8), 474. https://doi.org/10.3390/a18080474