Based on the background of system intelligence in the Internet of things era, this paper applied the design field of interaction design and user experience in the early days, and conducted further in-depth investigation through a large number of case studies and the use of quantitative and qualitative investigation methods. Based on this, the theories and strategies of the interaction design between enterprise members and intelligent machines were put forward and tested by actual design. At present, air pollution, energy shortage, and other issues are becoming more and more prominent, and calls for energy conservation, emission reduction, strengthening corporate social responsibility, and reducing the impact of economic development on the environment and society are growing. Therefore, companies must rethink their strategies and adapt their supply chains. Based on limited resources, enterprise machines have traditionally acted as a tool or a communication tool for a person. Yet, at the same time as the economy develops, the direct interaction between human and machine gradually emerges, and the economic development of an enterprise is bound to contradict environmental protection and social responsibility. Therefore, for enterprises, in different periods, different priority strategies will be adopted for the three dimensions of economy, environment, and society. The results showed that the economic benefit has increased by about 30% or more, and the ecological pollution has been reduced by about 40% on the original basis. Under the action of a sustainable supply chain, consumer satisfaction tends to be full and can be maintained at about 97%. In this context, the comparative analysis of the strategic optimization of enterprises in the supply chain is the focus of this thesis.
CITATION STYLE
Wang, L. W., Hung, C. C., & Hsieh, C. T. (2022). Security Strategy Optimization and Algorithm Based on 3D Economic Sustainable Supply Chain. Scientific Programming, 2022. https://doi.org/10.1155/2022/9972658
Mendeley helps you to discover research relevant for your work.