Abstract
Along with global geopolitical complex, information network security issues and increased natural disasters, risk management should be well considered in the construction material industry to re-integrate and establish stiff and flexible supply chains in order to cope with emergencies in the future market. Taking the construction material industry in Taiwan as the research object, representative enterprises with artificial intelligence applied sustainable supply chain management are studied. With the Delphi method and data envelopment analysis, the public data of annual statistics reports of the enterprises are used for selecting the performance indicators of inputs and outputs. Empirical data analysis is also performed to provide reference for the improvement. The research results are summarized as follows. 1. Substituting various input/output index values into CCR and BCC models, the overall production efficiency and pure technical efficiency of enterprises are calculated; by dividing the two, the returns to scale of enterprises are acquired. 2. Critical factors in artificial intelligence applied sustainable supply chain management could be found out through sensitivity analysis. Using the rate of sensitivity change as the evaluation baseline, sensitive factors contain financial aspect, scale aspect, financial performance, and profit before tax. Finally, discussions are proposed according to the results, expecting to help domestic businesses in the construction material industry establish steady and flexible supply chains and present diversified procurement sources to reinforce the emergency defensive ability of the construction material industry.
Highlights
All activities from the acquisition of raw materials to the sale of final products or semi-finished products to their delivery to customers are realized through the establishment of the global supply chain system; the gradual completeness of the logistics of transport and storage as well as the related businesses makes the trend of global supply chains become obvious
Artificial intelligence applied sustainable supply chain management is affected by external stakeholders to result in major changes in the sustainability measures and requirements for the artificial intelligence in the supply chain and further affect the sustainable development implementation and strategies in the construction materials industry
From the efficiency acquired from Data envelopment analysis (DEA) and the information of variables, one DMU, about 8% of all DMUs, shows strong-form performance efficiency on the artificial intelligence applied sustainable supply chain management, revealing the better efficiency in the execution of artificial intelligence applied sustainable supply chain management
Summary
All activities from the acquisition of raw materials to the sale of final products or semi-finished products to their delivery to customers are realized through the establishment of the global supply chain system; the gradual completeness of the logistics of transport and storage as well as the related businesses makes the trend of global supply chains become obvious. The advantages of cost competitiveness and constant regional economic growth result in the diversified global supply chains in Asian markets. China has played the core role in global supply chains. The low manpower and high productivity offered for enterprises from various countries and the lower logistics and coordination costs allow the costs of the domestic production or manufacturing to be far lower than those in other countries. It results in many enterprises moving the manufacturing to developing countries, similar to Mainland China, in Asia to increase single-country or region supply chains.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
