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De-risking procurement by digitalising spend monitoring

Banerjee, Shouvik - In: Journal of supply chain management, logistics and … 4 (2022) 4, pp. 331-343

Persistent link: https://www.econbiz.de/10013448077

Artificial intelligence technologies in international management

Aizenberh, Tetiana - In: Ekonomičnyj visnyk universytetu : zbirnyk naukovych … 19 (2024) 1, pp. 34-43

business process automation, document processing, inventory management, logistics, customer communications, analytics and … forecasting, and human resources management. Automation of processes has reduced costs and improved the quality of service …

Persistent link: https://www.econbiz.de/10015402840

How machine learning can improve decisions and automate manual processes in freight forwarding

Palke, Ksenia; Lunderman, Spence - In: Journal of supply chain management, logistics and … 5 (2022/2023) 3, pp. 202-211

Persistent link: https://www.econbiz.de/10014313021

Powering retailers' digitization through analytics and automation

Simchi-Levi, David; Wu, Michelle Xiao - In: International journal of production research 56 (2018) 1/2, pp. 809-816

Persistent link: https://www.econbiz.de/10011877132

Handbook of Smart Energy Systems

Fathi, Michel (ed.); Zio, Enrico (ed.); … - 2023

A Stackelberg Game-Theoretic Model of Fee-and-Rebate Pricing in a Load-Reduction Emergency Demand Response Program -- Planning to Incorporate Energy Conservation Practices, Renewable Energy Production Systems, and Eco-friendly Building Design Practices to Support Sustainability in US Public...

Persistent link: https://www.econbiz.de/10014322115

Handbook of Smart Energy Systems

Fathi, Mahdi (ed.); Zio, Enrico (ed.); … - 2021

A Stackelberg Game-Theoretic Model of Fee-and-Rebate Pricing in Load-Reduction Emergency Demand Response Program -- The forecasting of Turkey’s primary energy resources by LR Fuzzy numbered-Multivariate Autoregressive Model -- IoT Integration with Smart Grid Using Decentralization Technology...

Persistent link: https://www.econbiz.de/10014227478

Evaluating early predictive performance of machine learning approaches for engineering change schedule : a case study using predictive process monitoring techniques

Radišić-Aberger, Ognjen; Burggräf, Peter; Steinberg, … - In: Supply chain analytics 8 (2024), pp. 1-35

By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering change (EC) process. Here, failing to adhere to planned...

Persistent link: https://www.econbiz.de/10015325099

Machine learning in business process monitoring : a comparison of deep learning and classical approaches used for outcome prediction

Kratsch, Wolfgang; Manderscheid, Jonas Hans; … - In: Business & information systems engineering 63 (2021) 3, pp. 261-276

Persistent link: https://www.econbiz.de/10012542845

Combining machine learning and optimization for the operational patient-bed assignment problem

Schäfer, Fabian; Walther, Manuel; Grimm, Dominik; … - In: Health care management science : a new journal serving … 26 (2023) 4, pp. 785-806

Persistent link: https://www.econbiz.de/10015079830

Predicting an ICT business process innovation as a digital transformation with machine learning techniques

Eom, Taeung; Woo, Chungwon; Chun, Dongphil - In: Technology analysis & strategic management 36 (2024) 9, pp. 2271-2283

Persistent link: https://www.econbiz.de/10015108176