Economic complexity based recommendation enhance the efficiency of the belt and road initiative
- Liao, Hao Laboratory on Big data Application, College of Computer Science, Shenzhen University, China
- Huang, Xiao-Min Laboratory on Big data Application, College of Computer Science, Shenzhen University, China
- Vidmer, Alexandre Laboratory on Big data Application, College of Computer Science, Shenzhen University, China
- Zhang, Yi-Cheng Laboratory on Big data Application, College of Computer Science, Shenzhen University, China - Department of Physics, University of Fribourg, Switzerland
- Zhou, Ming-Yang Laboratory on Big data Application, College of Computer Science, Shenzhen University, China
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19.09.2018
Published in:
- Entropy. - 2018, vol. 20, no. 9, p. 718
English
The Belt and Road initiative (BRI) was announced in 2013 by the Chinese government. Its goal is to promote the cooperation between European and Asian countries, as well as enhancing the trust between members and unifying the market. Since its creation, more and more developing countries are joining the initiative. Based on the geographical location characteristics of the countries in this initiative, we propose an improvement of a popular recommendation algorithm that includes geographic location information. This recommendation algorithm is able to make suitable recommendations of products for countries in the BRI. Then, Fitness and Complexity metrics are used to evaluate the impact of the recommendation results and measure the country’s competitiveness. The aim of this work is to provide countries’ insights on the ideal development direction. By following the recommendations, the countries can quickly increase their international competitiveness.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Physique
- Language
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- English
- Classification
- Economics
- License
- License undefined
- Identifiers
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- RERO DOC 323893
- DOI 10.3390/e20090718
- Persistent URL
- https://folia.unifr.ch/unifr/documents/307548
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