The textiles and apparel industry is a major contributor to economic development while at the same time being one of the most polluting industries due to its lengthy supply chain and resource intensive production operations. To address these sustainability challenges, digitalization is seen as one of …

Purpose This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations …

This master’s thesis focuses on the implementation of a customized advanced controller for a gantry robot. Using mathematical models and numerical simulations, a Model Reference Adaptive Controller (MRAC) was selected. The controller was implemented on a Beckhoff-oriented system and validated on a physical …

Organizations feel an urgency to develop and implement applications based on foundation models: AI-models that have been trained on large-scale general data and can be finetuned to domain-specific tasks. In this process organizations face many questions, regarding model training and deployment, but also …

The sustainability transitions in our society requires deliberate collective action from multiple organisations. This implies a need to develop and implement new business models and re-design value networks. Collaborative sustainable business modelling (CSBM) is often proposed to fill this gap. CSBM …

In recent years, drones have increasingly supported First Responders (FRs) in monitoring incidents and providing additional information. However, analysing drone footage is time-intensive and cognitively demanding. In this research, we investigate the use of AI models for the detection of humans in drone …

This study proposes a novel loss function for neural network models that explores the topological structure of stock realized volatility (RV) data by adding Wasserstein Distance (WD). The study shows that the proposed loss statistically significantly improves the forecast accuracy of neural network models …

The developments in city logistics are leading to an increasing number of smaller, time-sensitive deliveries. The parcel market has consistently grown over the past decade, with emerging business models such as ship-from-store (both B2C and B2B) and quick commerce. Moreover, companies are increasingly …

Amidst escalating environmental and social challenges, this study explores regenerative business models’ definition and characteristics. While sustainable models have made considerable strides in research, policy, and practice, the advent of regenerative business models offers a progressive leap forward. …

This paper presents user-friendly code for the implementation of a loss function for neural network time series models that exploits the topological structures of financial data. By leveraging the recently-discovered presence of topological features present in financial time series data, the code offers …