This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for supply chain management. They present business models and investment options for enhanced strategic decision making as well as recent approaches for supply...

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for supply chain management. They present business models and investment options for enhanced strategic decision making as well as recent approaches for supply...

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for supply chain management. They present business models and investment options for enhanced strategic decision making as well as recent approaches for supply...

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for supply chain management. They present business models and investment options for enhanced strategic decision making as well as recent approaches for supply...

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for logistics and supply chain management. They present opportunities for enhancing resilience and sustainability as well as recent approaches for supply chain...

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for logistics and supply chains. They present business models and investment options for enhanced strategic decision making as well as recent approaches for...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...

We investigate heterogenous employment effects of Flemish training programmes. Based on administrative individual data, we analyse programme effects at various aggregation levels using Modified Causal Forests (MCF), a causal machine learning estimator for multiple programmes. While all...

We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Carlo Study that relies on arguably realistic data generation processes (DGPs) based on actual data. We consider 24...