Loading…
Using machine learning for evaluating global expansion location decisions: An analysis of Chinese manufacturing sector
•We study location decisions of Chinese manufacturing firm while expansion.•Novel machine learning (ML) tools have been used to evaluate location decisions.•ML algorithms reaffirm the relevance of financial leverage.•Firm size has positive but wage level has negative effect on location decisions. It...
Saved in:
Published in: | Technological forecasting & social change 2021-02, Vol.163, p.120436, Article 120436 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | •We study location decisions of Chinese manufacturing firm while expansion.•Novel machine learning (ML) tools have been used to evaluate location decisions.•ML algorithms reaffirm the relevance of financial leverage.•Firm size has positive but wage level has negative effect on location decisions.
It is now an acknowledged fact that the Fourth Industrial Revolution, and the advent of other associated technologies, mainly machine learning, are drastically changing the evolutionary framework of corporate decision making. Therefore, this research studies the location decision of Chinese companies in the global network, by using novel machine learning based framework and techniques. These include the 3D vision of mode network, heat map and the hierarchical cluster analysis, with the following support of neural network, and by incorporating the internet intensity as a proxy of the Fourth Industrial Revolution. These machine learning based algorithms reaffirm the relevance of classical variables, such as financial leverage and wage level, for the expansion decisions by Chinese companies. Our results assert that financial leverage has a negative effect on the location decision of companies in the global network. However, these connotations can be mitigated through the interaction of leverage with the firm size that yields a positive effect on the location decision. Moreover, the wage level, through its interaction with financial leverage, is able to exert a negative effect on the location decision. Finally, the effect of the probability, of the involvement in different behavioral clusters on diversification of internet intensity, is further analyzed by machine learning that is based on the neural network. |
---|---|
ISSN: | 0040-1625 1873-5509 |
DOI: | 10.1016/j.techfore.2020.120436 |