E3S Web Conf.
Volume 214, 20202020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|Number of page(s)||5|
|Section||Machine Learning and Energy Industry Structure Forecast Analysis|
|Published online||07 December 2020|
Simulation Analysis of Opportunity Recognition Path of Small and Medium-Sized Manufacturing Enterprises in Dongguan —— Comparison between E-commerce and Traditional Relationship Network
1 School of Management Xinhua College of Sun Yat-sen University Guangzhou, China
2 School of Management Macau University of Science and Technology Macau, China
Small and medium-sized manufacturing enterprises in Dongguan use e-commerce and traditional relationship networks to build paths for market opportunity recognition. Taking the company’s monthly average total sales and total capacity as variables, this article employs particle swarm optimization (PSO) to simulate the paths of opportunity recognition in three different modes, namely the single e-commerce mode, the single traditional relationship network and their hybrid mode. The results reveal that: for the single ecommerce mode, the capacity utilization rate is very low; for the single traditional relationship network, changes in learning factor will not affect the choices of the enterprises; for the hybrid mode, the optimal solution of the three models is reached. But there is a substitution between the enterprise’s own learning factor and the group learning factor, which leads to deviation from the optimal solution
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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