Determinants of the Marketing Budget Allocation Process across Countries Using Artificial Neural Network Classification: Japan, Germany, United States: An Abstract

2020 ◽  
pp. 247-248
Author(s):  
David J. Smith
Keyword(s):  
Neural Network ◽  
United States ◽  
Artificial Neural Network ◽  
Budget Allocation ◽  
Neural Network Classification ◽  
Allocation Process ◽  
Artificial Neural ◽  
Marketing Budget

scholarly journals The United States’ Clothing Imports from Asian Countries along the Belt and Road: An Extended Gravity Trade Model with Application of Artificial Neural Network

2020 ◽  
Vol 12 (18) ◽  
pp. 7433
Author(s):  
Danny Chi Kuen Ho ◽  
Eve Man Hin Chan ◽  
Tsz Leung Yip ◽  
Chi-Wing Tsang
Keyword(s):  
Neural Network ◽  
United States ◽  
Artificial Neural Network ◽  
Developing Countries ◽  
Trade Flow ◽  
The United States ◽  
Extended Gravity ◽  
Belt And Road ◽  
Artificial Neural ◽  
The Belt And Road

In 2013, China announced the Belt and Road Initiative (BRI), which aims to promote the connectivity of Asia, Europe, and Africa and deepen mutually beneficial economic cooperation among member countries. Past studies have reported a positive impact of the BRI on trade between China and its partner countries along the Belt and Road (B&R). However, less is known about its effect on the sectoral trade between the B&R countries and countries that show little support of the BRI. To address that gap, this study examines the changing patterns of clothing imports by the United States (US) from China and 14 B&R countries in Asia. An extended gravity model with a policy variable BRI is built to explain bilateral clothing trade flow. A panel regression model and artificial neural network (ANN) are developed based on the data collected from 1998 to 2018 and applied to predict the trade pattern of 2019. The results show a positive effect of the BRI on the clothing exports of some Asian developing countries along the B&R to the US and demonstrate the superior predictive power of the ANN. More research is needed to examine the balance between economic growth and the social and environmental sustainability of developing countries and to apply more advanced machine learning algorithms to examine global trade flow under the BRI.

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