Big data analytics in logistics and supply chain management: Certain investigations for research and applications
The amount of data produced and communicated over the Internet is significantly increasing,
thereby creating challenges for the organizations that would like to reap the benefits from …
thereby creating challenges for the organizations that would like to reap the benefits from …
Applications of artificial intelligence in inventory management: A systematic review of the literature
Today, companies that want to keep up with technological development and globalization
must be able to effectively manage their supply chains to achieve high quality, increased …
must be able to effectively manage their supply chains to achieve high quality, increased …
An optimized model using LSTM network for demand forecasting
H Abbasimehr, M Shabani, M Yousefi - Computers & industrial engineering, 2020 - Elsevier
In a business environment with strict competition among firms, accurate demand forecasting
is not straightforward. In this paper, a forecasting method is proposed, which has a strong …
is not straightforward. In this paper, a forecasting method is proposed, which has a strong …
A comparative study of demand forecasting models for a multi-channel retail company: a novel hybrid machine learning approach
A Mitra, A Jain, A Kishore, P Kumar - Operations research forum, 2022 - Springer
Demand forecasting has been a major concern of operational strategy to manage the
inventory and optimize the customer satisfaction level. The researchers have proposed …
inventory and optimize the customer satisfaction level. The researchers have proposed …
A big data driven framework for demand-driven forecasting with effects of marketing-mix variables
This study aims to investigate the contributions of promotional marketing activities, historical
demand and other factors to predict, and develop a big data-driven fuzzy classifier-based …
demand and other factors to predict, and develop a big data-driven fuzzy classifier-based …
Application areas and antecedents of automation in logistics and supply chain management: a conceptual framework
One of the main challenges for modern logistics and supply chain management (LSCM) is
the automation of processes along the supply chain. Although research on different …
the automation of processes along the supply chain. Although research on different …
Advanced predictive-analysis-based decision support for collaborative logistics networks
Purpose–The purpose of this paper is to examine challenges and potential of big data in
heterogeneous business networks and relate these to an implemented logistics solution …
heterogeneous business networks and relate these to an implemented logistics solution …
Big data analytics for supply chain transformation: A systematic literature review using scor framework
Recent developments in information technology generating massive amount of data are
referred to as big data. Such data with variety and velocity pose a challenge to supply chain …
referred to as big data. Such data with variety and velocity pose a challenge to supply chain …
Execution of omni-channel retailing based on a practical order fulfillment policy
With the rapid development of the retail industry and its transition to omni-channel, a critical
challenge that how to fulfill customer orders by choosing the proper channels arises for the …
challenge that how to fulfill customer orders by choosing the proper channels arises for the …
A Novel LSTM-GRU-Based Hybrid Approach for Electrical Products Demand Forecasting.
A Jadli, EHB Lahmer - International Journal of Intelligent …, 2022 - search.ebscohost.com
Demand forecasting is an indispensable key to planning and achieving objectives, as it
feeds all the processes in the company's supply chain. Forecasting is a difficult task that …
feeds all the processes in the company's supply chain. Forecasting is a difficult task that …