Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry

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...

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Autores principales:	Kuang-Sheng Liu, Ming-Hung Lin
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	artificial intelligence sustainable supply chain management performance assessment construction material industry Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/909e0a62c4184789a77e933edaa4f6a8
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id	oai:doaj.org-article:909e0a62c4184789a77e933edaa4f6a8
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spelling	oai:doaj.org-article:909e0a62c4184789a77e933edaa4f6a82021-11-25T19:04:10ZPerformance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry10.3390/su1322127672071-1050https://doaj.org/article/909e0a62c4184789a77e933edaa4f6a82021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12767https://doaj.org/toc/2071-1050Along 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.Kuang-Sheng LiuMing-Hung LinMDPI AGarticleartificial intelligencesustainable supply chain managementperformance assessmentconstruction material industryEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12767, p 12767 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial intelligence sustainable supply chain management performance assessment construction material industry Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	artificial intelligence sustainable supply chain management performance assessment construction material industry Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Kuang-Sheng Liu Ming-Hung Lin Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry
description	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.
format	article
author	Kuang-Sheng Liu Ming-Hung Lin
author_facet	Kuang-Sheng Liu Ming-Hung Lin
author_sort	Kuang-Sheng Liu
title	Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry
title_short	Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry
title_full	Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry
title_fullStr	Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry
title_full_unstemmed	Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry
title_sort	performance assessment on the application of artificial intelligence to sustainable supply chain management in the construction material industry
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/909e0a62c4184789a77e933edaa4f6a8
work_keys_str_mv	AT kuangshengliu performanceassessmentontheapplicationofartificialintelligencetosustainablesupplychainmanagementintheconstructionmaterialindustry AT minghunglin performanceassessmentontheapplicationofartificialintelligencetosustainablesupplychainmanagementintheconstructionmaterialindustry
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Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry

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