Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system
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DOI: 10.1016/j.ijpe.2019.107519
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- Xin Yao & Yuanyuan Cheng & Li Zhou & Malin Song, 2022. "Green efficiency performance analysis of the logistics industry in China: based on a kind of machine learning methods," Annals of Operations Research, Springer, vol. 308(1), pages 727-752, January.
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- Govindan, Kannan & Kannan, Devika & Jørgensen, Thomas Ballegård & Nielsen, Tim Straarup, 2022. "Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
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- Li, Xishu & Yin, Ying & Manrique, David Vergara & Bäck, Thomas, 2021. "Lifecycle forecast for consumer technology products with limited sales data," International Journal of Production Economics, Elsevier, vol. 239(C).
- Rodríguez-Espíndola, Oscar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel & Emrouznejad, Ali, 2022. "Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
- Stekelorum, Rebecca & Laguir, Issam & Gupta, Shivam & Kumar, Sameer, 2021. "Green supply chain management practices and third-party logistics providers’ performances: A fuzzy-set approach," International Journal of Production Economics, Elsevier, vol. 235(C).
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Keywords
Industry 4.0; Bass diffusion model; Information sharing; Reverse logistics; Inventory and production planning;All these keywords.
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