The impact of digital technologies on operational causes of the bullwhip effect–a literature review
M Wiedenmann, A Größler - Procedia CIRP, 2019 - Elsevier
The digital transformation affects individuals, businesses as well as society as a whole.
Supply chains are no exception when it comes to the substantial impact of this …
Supply chains are no exception when it comes to the substantial impact of this …
Data Science Applications in Circular Economy: Trends, Status, and Future
The circular economy (CE) aims to decouple the growth of the economy from the
consumption of finite resources through strategies, such as eliminating waste, circulating …
consumption of finite resources through strategies, such as eliminating waste, circulating …
[PDF][PDF] Comparative analysis of short-term demand predicting models using ARIMA and deep learning
H Bousqaoui, I Slimani… - International Journal of …, 2021 - pdfs.semanticscholar.org
The forecasting consists of taking historical data as inputs then using them to predict future
observations, thus determining future trends. Demand prediction is a crucial component in …
observations, thus determining future trends. Demand prediction is a crucial component in …
Anomaly detection using long short term memory networks and its applications in supply chain management
Anomaly detection has been becoming an important problem in several domains. In this
paper, we propose a new method to detect anomalies in time series based on Long Short …
paper, we propose a new method to detect anomalies in time series based on Long Short …
Macroscopic big data analysis and prediction of driving behavior with an adaptive fuzzy recurrent neural network on the internet of vehicles
DC Li, MYC Lin, LD Chou - IEEE Access, 2022 - ieeexplore.ieee.org
Dangerous driving behaviors are diverse and complex. Determining how to analyze the
driving behavior of public drivers objectively and accurately has always been a research …
driving behavior of public drivers objectively and accurately has always been a research …
A neural network approach for retailer risk assessment in the aftermarket industry
Purpose Given the competitive environment and complicated relationships in supply chains
in the modern era, it is important to take into account internal and external risks. In addition …
in the modern era, it is important to take into account internal and external risks. In addition …
Modeling and analyzing the inventory level for demand uncertainty in the VUCA world: evidence from biomedical manufacturer
P Raghuram, S Bhupesh, R Manivannan… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
As the world is witnessing unprecedented events such as the COVID-19 pandemic, we live
in a volatile, uncertain, complex, ambiguity (VUCA) world. Where volatility in supplies …
in a volatile, uncertain, complex, ambiguity (VUCA) world. Where volatility in supplies …
[HTML][HTML] Forecasting supply chain demand approach using knowledge management processes and supervised learning techniques
In today's context (competition and knowledge economy), ML and KM on the supply chain
level have received increased attention aiming to determine long and short-term success of …
level have received increased attention aiming to determine long and short-term success of …
[HTML][HTML] Comparison of deep and conventional machine learning models for prediction of one supply chain management distribution cost
X Yu, L Tang, L Long, M Sina - Scientific Reports, 2024 - nature.com
Strategic supply chain management (SCM) is essential for organizations striving to optimize
performance and attain their goals. Prediction of supply chain management distribution cost …
performance and attain their goals. Prediction of supply chain management distribution cost …
Method for travel time prediction in emerging markets based on anonymous truck GPS data
CM Pérez-González, J Mora-Vargas… - Annals of Operations …, 2024 - Springer
Travel time pattern analysis and prediction are essential for achieving better logistics
performance in the supply chain. Solid theoretical assumptions based on reliable historical …
performance in the supply chain. Solid theoretical assumptions based on reliable historical …