Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities
M Seyedan, F Mafakheri - Journal of Big Data, 2020 - Springer
Big data analytics (BDA) in supply chain management (SCM) is receiving a growing
attention. This is due to the fact that BDA has a wide range of applications in SCM, including …
attention. This is due to the fact that BDA has a wide range of applications in SCM, including …
Data science and big data analytics: A systematic review of methodologies used in the supply chain and logistics research
Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …
extensively in supply chains and logistics (SC &L). However, the existing insights are …
[HTML][HTML] Time-series forecasting of seasonal items sales using machine learning–A comparative analysis
There has been a growing interest in the field of neural networks for prediction in recent
years. In this research, a public dataset including the sales history of a retail store is …
years. In this research, a public dataset including the sales history of a retail store is …
Assessing the feasibility of hyperlocal delivery model as an effective distribution channel
Purpose The successive waves of the Covid-19 SARS-II pandemic and the attendant
lockdown imposed by the governments worldwide drove the economic activities to a halt …
lockdown imposed by the governments worldwide drove the economic activities to a halt …
Daily retail demand forecasting using machine learning with emphasis on calendric special days
J Huber, H Stuckenschmidt - International Journal of Forecasting, 2020 - Elsevier
Demand forecasting is an important task for retailers as it is required for various operational
decisions. One key challenge is to forecast demand on special days that are subject to vastly …
decisions. One key challenge is to forecast demand on special days that are subject to vastly …
A data-driven newsvendor problem: From data to decision
J Huber, S Müller, M Fleischmann… - European Journal of …, 2019 - Elsevier
Retailers that offer perishable items are required to make ordering decisions for hundreds of
products on a daily basis. This task is non-trivial because the risk of ordering too much or too …
products on a daily basis. This task is non-trivial because the risk of ordering too much or too …
[HTML][HTML] A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks
The unexpected emergence of the COVID-19 pandemic has changed how grocery shopping
is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in …
is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in …
[HTML][HTML] Forecasting demand profiles of new products
RM Van Steenbergen, MRK Mes - Decision support systems, 2020 - Elsevier
Nowadays, many companies face shorter product life cycles, increasing the need to properly
forecast demand for newly introduced products. These forecasts allow them to support …
forecast demand for newly introduced products. These forecasts allow them to support …
A multivariate approach for multi-step demand forecasting in assembly industries: Empirical evidence from an automotive supply chain
JNC Gonçalves, P Cortez, MS Carvalho… - Decision Support …, 2021 - Elsevier
Demand forecasting works as a basis for operating, business and production planning
decisions in many supply chain contexts. Yet, how to accurately predict the manufacturer's …
decisions in many supply chain contexts. Yet, how to accurately predict the manufacturer's …
Demand forecasting in supply chains: a review of aggregation and hierarchical approaches
Demand forecasts are the basis of most decisions in supply chain management. The
granularity of these decisions lead to different forecast requirements. For example, inventory …
granularity of these decisions lead to different forecast requirements. For example, inventory …