The Assessment of Big Data Analytics Based Supply Chain Resilience: A comprehensive tool to assess and benchmark the level of supply chain resilience based on big data analytics enablers in the FMCG industry

Big data analytics (BDA) and supply chain resilience are both present and important topics, but research on the relation between the subjects is limited. This also holds for the translation of the subject for a specific industry. This research therefore addresses this relation and translates it to a comprehensive partial resilience assessment...

Prediction of voltage distribution using deep learning and identified key smart meter locations

The energy landscape for the Low-Voltage (LV) networks is undergoing rapid changes. These changes are driven by the increased penetration of distributed Low Carbon Technologies, both on the generation side (i.e. adoption of micro-renewables) and demand side (i.e. electric vehicle charging). The previously passive ‘fit-and-forget’ approach to...

Towards big data analytics embedment in business operations: Perceiving trade‐offs between conflicting capabilities for embedding Big Data Analytics

Due to the popularity and complexity of Big Data Analytics (BDA), numerous articles have been published about embedding BDA in business operations. What they have in common is that they use the Resource Based View to assess where a firm need to be capable of to achieve this. However, in practice, capabilities for BDA can conflict with each other...

Developing an adoption process framework for Big Data Analytics by OEM companies

With the rapid growth of large amounts of data in different types from different sources, it is possible for the industrial automation sector to transform raw data from production processes into meaningful and useful information for business purpose. The leverage of Big Data Analytics helps the Original Equipment Manufacturing companies gain...