The state of artificial intelligence: Procurement versus sales and marketing
In: Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 31
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DOI: 10.15480/882.3990
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- Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
- Allal-Chérif, Oihab & Simón-Moya, Virginia & Ballester, Antonio Carlos Cuenca, 2021. "Intelligent purchasing: How artificial intelligence can redefine the purchasing function," Journal of Business Research, Elsevier, vol. 124(C), pages 69-76.
- Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
- Jonathan Z. Zhang & Oded Netzer & Asim Ansari, 2014. "Dynamic Targeted Pricing in B2B Relationships," Marketing Science, INFORMS, vol. 33(3), pages 317-337, May.
- Xu, Zhenning & Frankwick, Gary L. & Ramirez, Edward, 2016. "Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective," Journal of Business Research, Elsevier, vol. 69(5), pages 1562-1566.
- Alexandra Brintrup & Johnson Pak & David Ratiney & Tim Pearce & Pascal Wichmann & Philip Woodall & Duncan McFarlane, 2020. "Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3330-3341, June.
- Huber, Jakob & Stuckenschmidt, Heiner, 2020. "Daily retail demand forecasting using machine learning with emphasis on calendric special days," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1420-1438.
- Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
- Souza, Gilvan C., 2014. "Supply chain analytics," Business Horizons, Elsevier, vol. 57(5), pages 595-605.
- Nam, Dalwoo & Lee, Junyeong & Lee, Heeseok, 2019. "Business analytics use in CRM: A nomological net from IT competence to CRM performance," International Journal of Information Management, Elsevier, vol. 45(C), pages 233-245.
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Keywords
Artificial Intelligence; Blockchain;Statistics
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