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Predicting customer demand for remanufactured products: A data-mining approach

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  1. Narendra Singh & Pushpa Singh & Mukul Gupta, 2020. "An inclusive survey on machine learning for CRM: a paradigm shift," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 47(4), pages 447-457, December.
  2. Lee, Carmen Kar Hang & Leung, Eric Ka Ho, 2023. "Spatiotemporal analysis of bike-share demand using DTW-based clustering and predictive analytics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
  3. Zhai, Mengfan & Wang, Xinyue & Zhao, Xijie, 2024. "The importance of online customer reviews characteristics on remanufactured product sales: Evidence from the mobile phone market on Amazon.com," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
  4. Seoyoon Lee & Minjung Kwak, 2020. "Consumer Valuation of Remanufactured Products: A Comparative Study of Product Categories and Business Models," Sustainability, MDPI, vol. 12(18), pages 1-29, September.
  5. Sule Birim & Ipek Kazancoglu & Sachin Kumar Mangla & Aysun Kahraman & Yigit Kazancoglu, 2024. "The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods," Annals of Operations Research, Springer, vol. 339(1), pages 131-161, August.
  6. Meiling Zhou & Pin Zhou & Yuqing Xia & Xianpei Hong, 2025. "Demand Information Forecasting and Sharing in a Remanufacturing Closed‐Loop Supply Chain," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(2), pages 1062-1077, March.
  7. Christian Fieberg & Gerrit Liedtke & Thorsten Poddig, 2025. "Recurrent double-conditional factor model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 47(1), pages 205-254, March.
  8. Duan, Sophia Xiaoxia & Tay, Richard & Molla, Alemayehu & Deng, Hepu, 2022. "Predicting Mobility as a Service (MaaS) use for different trip categories: An artificial neural network analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 135-149.
  9. Mahmoud Tarhini, 2022. "Consumption and Consumer Behaviour of Organic AGRI-FOOD Products," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 23(1), pages 136-149, March.
  10. Gary Mena & Kristof Coussement & Koen W. Bock & Arno Caigny & Stefan Lessmann, 2024. "Exploiting time-varying RFM measures for customer churn prediction with deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 765-787, August.
  11. Xu, Shilin & Liu, Yang & Jin, Chun, 2023. "Forecasting daily tourism demand with multiple factors," Annals of Tourism Research, Elsevier, vol. 103(C).
  12. Fatemeh Ehsani & Monireh Hosseini, 2024. "Customer purchase prediction in electronic markets from clickstream data using the Oracle meta-classifier," Operational Research, Springer, vol. 24(1), pages 1-32, March.
  13. Bhattacharya, Sourabh & Govindan, Kannan & Ghosh Dastidar, Surajit & Sharma, Preeti, 2024. "Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
  14. Atiyeh Seifian & Sajjad Shokouhyar & Mohamad Bahrami, 2024. "Exploring customers’ purchasing behavior toward refurbished mobile phones: a cross-cultural opinion mining of amazon reviews," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 28131-28159, November.
  15. Adel A. Alamri, 2023. "A Sustainable Closed-Loop Supply Chains Inventory Model Considering Optimal Number of Remanufacturing Times," Sustainability, MDPI, vol. 15(12), pages 1-23, June.
  16. Dai, Hongyan & Xiao, Qin & Chen, Songlin & Zhou, Weihua, 2023. "Data-driven demand forecast for O2O operations: An adaptive hierarchical incremental approach," International Journal of Production Economics, Elsevier, vol. 259(C).
  17. Muhammad Salman Pathan & Edana Richardson & Edgar Galvan & Peter Mooney, 2023. "The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
  18. Huang, Shupeng & Potter, Andrew & Eyers, Daniel & Li, Qinyun, 2021. "The influence of online review adoption on the profitability of capacitated supply chains," Omega, Elsevier, vol. 105(C).
  19. Thuy, Arthur & Benoit, Dries F., 2024. "Explainability through uncertainty: Trustworthy decision-making with neural networks," European Journal of Operational Research, Elsevier, vol. 317(2), pages 330-340.
  20. Duong, Quang Huy & Zhou, Li & Van Nguyen, Truong & Meng, Meng, 2025. "Understanding and predicting online product return behavior: An interpretable machine learning approach," International Journal of Production Economics, Elsevier, vol. 280(C).
  21. Karina Cecilia Arredondo-Soto & Alejandro Jiménez-Zaragoza & Marco Augusto Miranda-Ackerman & Julio Blanco-Fernández & Alejandra García-Lechuga & Guadalupe Hernández-Escobedo & Jorge Luis García-Alcar, 2022. "Design and Repair Strategies Based on Product–Service System and Remanufacturing for Value Preservation," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
  22. Shushu Xie & Yingxue Zhao & Lin Zhao & Xingyuan He, 2024. "Do Online Reviews Always Incentivise Remanufacturers to Improve Quality in a Competitive Environment?," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(67), pages 903-903, August.
  23. Gang Chen & Lihua Huang & Shuaiyong Xiao & Chenghong Zhang & Huimin Zhao, 2024. "Attending to Customer Attention: A Novel Deep Learning Method for Leveraging Multimodal Online Reviews to Enhance Sales Prediction," Information Systems Research, INFORMS, vol. 35(2), pages 829-849, June.
  24. Boram Choi & Jong Hwan Suh, 2020. "Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
  25. Kusi-Sarpong, Simonov & Orji, Ifeyinwa Juliet & Gupta, Himanshu & Kunc, Martin, 2021. "Risks associated with the implementation of big data analytics in sustainable supply chains," Omega, Elsevier, vol. 105(C).
  26. Xu, Xianhao & Shen, Yaohan & (Amanda) Chen, Wanying & Gong, Yeming & Wang, Hongwei, 2021. "Data-driven decision and analytics of collection and delivery point location problems for online retailers," Omega, Elsevier, vol. 100(C).
  27. Dash, Raj & Bhattacharjee, Biplab, 2024. "Consumer uptake of energy-efficient appliances in India's online marketplace: An electronic word-of-mouth (eWOM) process model," Utilities Policy, Elsevier, vol. 88(C).
  28. Alyahya, Mansour & Agag, Gomaa & Aliedan, Meqbel & Abdelmoety, Ziad Hassan & Daher, Maya Mostafa, 2023. "A sustainable step forward: Understanding factors affecting customers’ behaviour to purchase remanufactured products," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
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