The integration of Industry 4.0 technologies is crucial for developing a robust supply chain management system in the production sector, significantly impacting technological advancements, infrastructure development, resource utilization, consumer acceptance, and policy formulation. This study presents and thoroughly examines novel hybrid decision-making techniques that combine the Analytic Hierarchy Process with the Technique for Order Preference by Similarity to Ideal Solution and VIKOR within a q-rung picture fuzzy framework. We frame the challenges associated with Industry 4.0 supply chain management in the production sector as a multi-criteria decision-making model, which we solve using the proposed hybrid approaches. Additionally, we explore the implications of adopting these methodologies in real-world scenarios, emphasizing their potential to enhance decision-making effectiveness. To enhance comprehension of the proposed model, we conduct sensitivity and comparative analyses, highlighting the advantages of the methodologies employed and demonstrating their applicability across various decision contexts.
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Jiangxi Univ Finance & Econ, Shenzhen Res Inst, Nanchang, Peoples R ChinaJiangxi Univ Finance & Econ, Shenzhen Res Inst, Nanchang, Peoples R China
Wan, Benting
Huang, Juelin
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Jiangxi Univ Finance & Econ, Sch Software & Internet Things Engn, Nanchang, Peoples R ChinaJiangxi Univ Finance & Econ, Shenzhen Res Inst, Nanchang, Peoples R China
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Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Xiao, Liming
Huang, Guangquan
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Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Huang, Guangquan
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Pedrycz, Witold
Pamucar, Dragan
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Univ Def Belgrade, Mil Acad, Dept Logist, Belgrade 11000, SerbiaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Pamucar, Dragan
Martinez, Luis
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Univ Jaen, Dept Comp Sci, Jaen 23071, SpainChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Martinez, Luis
Zhang, Genbao
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Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Chongqing Univ Arts & Sci, Sch Intelligent Mfg Engn, Chongqing 402160, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China