Cargando…
Industry Upgrading: Recommendations of New Products Based on World Trade Network
GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is findi...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514146/ https://www.ncbi.nlm.nih.gov/pubmed/33266755 http://dx.doi.org/10.3390/e21010039 |
_version_ | 1783586520760844288 |
---|---|
author | Zhang, Wen-Yao Chen, Bo-Lun Kong, Yi-Xiu Shi, Gui-Yuan Zhang, Yi-Cheng |
author_facet | Zhang, Wen-Yao Chen, Bo-Lun Kong, Yi-Xiu Shi, Gui-Yuan Zhang, Yi-Cheng |
author_sort | Zhang, Wen-Yao |
collection | PubMed |
description | GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its competitiveness. The proximity indicator measures the similarity between products and can be used to predict the probability that a country will develop a new industry. On the other hand, the Fitness–Complexity algorithm can help to find the important products and developing countries. In this paper, we find that the maximum of the proximity between a certain product and a country’s existing products is highly correlated with the probability that the country exports this new product in the next year. In addition, we find that the more products that are related to a certain product, the higher probability of the emergence of the new product. Finally, we combine the proximity indicator and the Fitness–Complexity algorithm and then attempt to provide a recommendation list of new products that can help developing countries to upgrade their industry. A few examples are given in the end. |
format | Online Article Text |
id | pubmed-7514146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75141462020-11-09 Industry Upgrading: Recommendations of New Products Based on World Trade Network Zhang, Wen-Yao Chen, Bo-Lun Kong, Yi-Xiu Shi, Gui-Yuan Zhang, Yi-Cheng Entropy (Basel) Article GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its competitiveness. The proximity indicator measures the similarity between products and can be used to predict the probability that a country will develop a new industry. On the other hand, the Fitness–Complexity algorithm can help to find the important products and developing countries. In this paper, we find that the maximum of the proximity between a certain product and a country’s existing products is highly correlated with the probability that the country exports this new product in the next year. In addition, we find that the more products that are related to a certain product, the higher probability of the emergence of the new product. Finally, we combine the proximity indicator and the Fitness–Complexity algorithm and then attempt to provide a recommendation list of new products that can help developing countries to upgrade their industry. A few examples are given in the end. MDPI 2019-01-09 /pmc/articles/PMC7514146/ /pubmed/33266755 http://dx.doi.org/10.3390/e21010039 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Wen-Yao Chen, Bo-Lun Kong, Yi-Xiu Shi, Gui-Yuan Zhang, Yi-Cheng Industry Upgrading: Recommendations of New Products Based on World Trade Network |
title | Industry Upgrading: Recommendations of New Products Based on World Trade Network |
title_full | Industry Upgrading: Recommendations of New Products Based on World Trade Network |
title_fullStr | Industry Upgrading: Recommendations of New Products Based on World Trade Network |
title_full_unstemmed | Industry Upgrading: Recommendations of New Products Based on World Trade Network |
title_short | Industry Upgrading: Recommendations of New Products Based on World Trade Network |
title_sort | industry upgrading: recommendations of new products based on world trade network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514146/ https://www.ncbi.nlm.nih.gov/pubmed/33266755 http://dx.doi.org/10.3390/e21010039 |
work_keys_str_mv | AT zhangwenyao industryupgradingrecommendationsofnewproductsbasedonworldtradenetwork AT chenbolun industryupgradingrecommendationsofnewproductsbasedonworldtradenetwork AT kongyixiu industryupgradingrecommendationsofnewproductsbasedonworldtradenetwork AT shiguiyuan industryupgradingrecommendationsofnewproductsbasedonworldtradenetwork AT zhangyicheng industryupgradingrecommendationsofnewproductsbasedonworldtradenetwork |