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Forecasting sales in the supply chain: Consumer analytics in the big data era

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Cited by:

  1. Andrew Manikas & Michael Godfrey & Jason Woldt, 2022. "What Drives Higher Beer Ratings? Evidence From Big Data," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 15(1), pages 1-13.
  2. Büttner, Daniel & Scheidler, Anne Antonia & Rabe, Markus, 2021. "A reference model for data-driven sales planning: Development of the model's framework and functionality," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 441-476, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
  3. Dinis, Duarte & Barbosa-Póvoa, Ana & Teixeira, Ângelo Palos, 2022. "Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems," International Journal of Forecasting, Elsevier, vol. 38(1), pages 178-192.
  4. Jeffrey A. Hoyle & Rebecca Dingus & J. Holton Wilson, 0. "An exploration of sales forecasting: sales manager and salesperson perspectives," Journal of Marketing Analytics, Palgrave Macmillan, vol. 0, pages 1-10.
  5. Terrance Jalbert & Jonathan D. Stewart, 2022. "A Comprehensive Retirement Financial Planning Tool," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 15(1), pages 47-76.
  6. Guiyu Bai & Wenjuan Wang & Xinxin Wang, 2022. "Research on the Influence of Technological Innovation Enthusiasm on Innovation Performance from the Perspective of Nonlinearity—Empirical Evidence from Chinese Listed Firms," Sustainability, MDPI, vol. 14(16), pages 1-14, August.
  7. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
  8. Anna Trunk & Hendrik Birkel, 2022. "No Resilience Without Partners: A Case Study on German Small and Medium-Sized Enterprises in the Context of COVID-19," Schmalenbach Journal of Business Research, Springer, vol. 74(4), pages 537-574, December.
  9. Patrick Brandtner & Farzaneh Darbanian & Taha Falatouri & Chibuzor Udokwu, 2021. "Impact of COVID-19 on the Customer End of Retail Supply Chains: A Big Data Analysis of Consumer Satisfaction," Sustainability, MDPI, vol. 13(3), pages 1-18, January.
  10. Liu, Zhenyuan & Han, Shuihua & Li, Chao & Gupta, Shivam & Sivarajah, Uthayasankar, 2022. "Leveraging customer engagement to improve the operational efficiency of social commerce start-ups," Journal of Business Research, Elsevier, vol. 140(C), pages 572-582.
  11. Vineet Paliwal & Shalini Chandra & Suneel Sharma, 2020. "Blockchain Technology for Sustainable Supply Chain Management: A Systematic Literature Review and a Classification Framework," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
  12. Omar, Haytham & Klibi, Walid & Babai, M. Zied & Ducq, Yves, 2023. "Basket data-driven approach for omnichannel demand forecasting," International Journal of Production Economics, Elsevier, vol. 257(C).
  13. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
  14. Christina Vasilopoulou & Leonidas Theodorakopoulos & Ioanna Giannoukou, 2023. "Big Data and Consumer Behavior: The Power and Pitfalls of Analytics in the Digital Age," Technium Social Sciences Journal, Technium Science, vol. 45(1), pages 469-480, July.
  15. Pascucci, Federica & Nardi, Lorenzo & Marinelli, Luca & Paolanti, Marina & Frontoni, Emanuele & Gregori, Gian Luca, 2022. "Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
  16. Anna Trunk & Hendrik Birkel & Evi Hartmann, 2020. "On the current state of combining human and artificial intelligence for strategic organizational decision making," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 875-919, November.
  17. Sohrabpour, Vahid & Oghazi, Pejvak & Toorajipour, Reza & Nazarpour, Ali, 2021. "Export sales forecasting using artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  18. Lalou Panagiota & Ponis Stavros T. & Efthymiou Orestis K., 2020. "Demand Forecasting of Retail Sales Using Data Analytics and Statistical Programming," Management & Marketing, Sciendo, vol. 15(2), pages 186-202, June.
  19. Micu, Adrian & Capatina, Alexandru & Cristea, Dragos Sebastian & Munteanu, Dan & Micu, Angela-Eliza & Sarpe, Daniela Ancuta, 2022. "Assessing an on-site customer profiling and hyper-personalization system prototype based on a deep learning approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  20. Jeffrey A. Hoyle & Rebecca Dingus & J. Holton Wilson, 2020. "An exploration of sales forecasting: sales manager and salesperson perspectives," Journal of Marketing Analytics, Palgrave Macmillan, vol. 8(3), pages 127-136, September.
  21. Shokouhyar, Sajjad & Ahmadi, Sadra & Ashrafzadeh, Mahdi, 2021. "Promoting a novel method for warranty claim prediction based on social network data," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  22. John Hamilton, 2020. "The Strategic Change Matrix and Business Sustainability across COVID-19," Sustainability, MDPI, vol. 12(15), pages 1-19, July.
  23. Erkip, Nesim Kohen, 2023. "Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems," European Journal of Operational Research, Elsevier, vol. 308(3), pages 949-959.
  24. Sebastian Vock & Laurie A. Garrow & Catherine Cleophas, 2022. "Clustering as an approach for creating data-driven perspectives on air travel itineraries," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 212-227, April.
  25. Roberto Casado-Vara & Angel Martin del Rey & Daniel Pérez-Palau & Luis de-la-Fuente-Valentín & Juan M. Corchado, 2021. "Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
  26. Mohammad Khajehzadeh & Farhad Pazhuheian & Farima Seifi & Rassoul Noorossana & Ali Asli & Niloufar Saeedi, 2022. "Analysis of Factors Affecting Product Sales with an Outlook toward Sale Forecasting in Cosmetic Industry using Statistical Methods," International Review of Management and Marketing, Econjournals, vol. 12(6), pages 55-63, November.
  27. Xu, Jinou & Pero, Margherita & Fabbri, Margherita, 2023. "Unfolding the link between big data analytics and supply chain planning," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
  28. Arpan Kumar Kar & Shalini Nath Tripathi & Nishtha Malik & Shivam Gupta & Uthayasankar Sivarajah, 2023. "How Does Misinformation and Capricious Opinions Impact the Supply Chain - A Study on the Impacts During the Pandemic," Annals of Operations Research, Springer, vol. 327(2), pages 713-734, August.
  29. Altay, Nezih & Narayanan, Arunachalam, 2022. "Forecasting in humanitarian operations: Literature review and research needs," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1234-1244.
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