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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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  • Kuang-Sheng Liu

    (Department of Interior Design, Tung-Fang Design University, Kaohsiung 829003, Taiwan)

  • Ming-Hung Lin

    (Graduate Institute of Cultural and Creative Design, Tung-Fang Design University, Kaohsiung 829003, Taiwan)

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.

Suggested Citation

  • Kuang-Sheng Liu & Ming-Hung Lin, 2021. "Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:22:p:12767-:d:682229
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    1. Qian Zheng & Manman Wang & Feng Yang, 2021. "Optimal Channel Strategy for a Fresh Produce E-Commerce Supply Chain," Sustainability, MDPI, vol. 13(11), pages 1-24, May.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Delbari, Seyyed Ali & Ng, Siew Imm & Aziz, Yuhanis Abdul & Ho, Jo Ann, 2016. "An investigation of key competitiveness indicators and drivers of full-service airlines using Delphi and AHP techniques," Journal of Air Transport Management, Elsevier, vol. 52(C), pages 23-34.
    4. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Frank Werner & Marina Ivanova, 2016. "A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 386-402, January.
    5. Carina L. Gargalo & Eduardo Pereda Pons & Ana Paula Barbosa-Povoa & Ana Carvalho, 2021. "A Lean Approach to Developing Sustainable Supply Chains," Sustainability, MDPI, vol. 13(7), pages 1-33, March.
    6. Yanjie Wu & Sujuan Wang, 2021. "Sustainable Market Entry Strategy under a Supply Chain Environment," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
    7. Mensah, Ishmael & Dei Mensah, Rebecca, 2018. "Effects of Service Quality and Customer Satisfaction on Repurchase Intention in Restaurants on University of Cape Coast Campus," MPRA Paper 88449, University Library of Munich, Germany.
    8. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    9. Mishra, Mukunda & Chatterjee, Soumendu, 2018. "Application of Analytical Hierarchy Process (AHP) algorithm to income insecurity susceptibility mapping – A study in the district of Purulia, India," Socio-Economic Planning Sciences, Elsevier, vol. 62(C), pages 56-74.
    10. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    11. Chih-Hung Hsu & An-Yuan Chang & Ting-Yi Zhang & Wei-Da Lin & Wan-Ling Liu, 2021. "Deploying Resilience Enablers to Mitigate Risks in Sustainable Fashion Supply Chains," Sustainability, MDPI, vol. 13(5), pages 1-24, March.
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