Jens Strüker

TL;DR: This research presents novel ways to personalize the relationship with customers without sacrificing their privacy through the use of artificial intelligence, machine learning and other technologies.

TL;DR: This case study analyzes the impact of theory-based factors on the implementation of different blockchain technologies in use cases from the energy sector using an integrated research model based on the Diffusion of Innovations theory, institutional economics and the Technology-Organization-Environment framework.

TL;DR: It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology to improve energy efficiency and to integrate decentralized renewable energy sources into the power grid.

TL;DR: A framework that combines the benefit evaluation steps of identification, forecasting and assessment is introduced and six types of RFID benefits are derived that support the systematic identification of benefits, as well as the selection of forecast and assessment methods.

TL;DR: This paper uses state-of-the-art forecasting tools, in particular support vector machines and neural networks, to evaluate the use of disaggregated smart home sensor data for household-level demand forecasting and shows that having more sensors appears to be more valuable than increasing the time resolution of measurements.