Next Article in Journal
Three Techniques for Enhancing Chaos-Based Joint Compression and Encryption Schemes
Previous Article in Journal
Fourier Transform on the Homogeneous Space of 3D Positions and Orientations for Exact Solutions to Linear PDEs
Previous Article in Special Issue
Unfolding the Complexity of the Global Value Chain: Strength and Entropy in the Single-Layer, Multiplex, and Multi-Layer International Trade Networks
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Entropy 2019, 21(1), 39; https://doi.org/10.3390/e21010039

Industry Upgrading: Recommendations of New Products Based on World Trade Network

1
Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 23303, China
2
Department of Physics, University of Fribourg, 1700 Fribourg, Switzerland
*
Author to whom correspondence should be addressed.
Received: 31 July 2018 / Revised: 20 November 2018 / Accepted: 4 January 2019 / Published: 9 January 2019
(This article belongs to the Special Issue Economic Fitness and Complexity)
Full-Text   |   PDF [500 KB, uploaded 9 January 2019]   |  

Abstract

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. View Full-Text
Keywords: economic complexity; proximity; industry upgrading economic complexity; proximity; industry upgrading
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhang, W.-Y.; Chen, B.-L.; Kong, Y.-X.; Shi, G.-Y.; Zhang, Y.-C. Industry Upgrading: Recommendations of New Products Based on World Trade Network. Entropy 2019, 21, 39.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top