The digital transition of the economy is widely expected to change the nature of work. This may happen both through creating new digital job profiles, and by digitising existing jobs. As these changes unfold, new digital skills may be needed at the workplace. We track the trends in demand for...

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...

Purpose: This analysis aims to develop a conceptual framework for the adoption of blockchain-based solutions in maritime logistics. Using the application area of maritime cold chains, we examine which characteristics are crucial for the use of blockchain and which requirements need to be met for...

Purpose: Smart contracts are transaction programs with an 'if-then logic' in relation to the blockchain technology and offer new possibilities for production control. Smart orders are derived from production orders and they are based on smart contracts. Therefore, they are created with the...

Purpose: Object detection is rapidly evolving through machine learning technology in automation systems. Well prepared data is necessary to train the algorithms. Accordingly, the objective of this paper is to describe a re-evaluation of the so-called Logistics Objects in Context (LOCO) dataset,...

Purpose: This publication investigates preliminary data quality analyses to estimate the efforts and expected results of the use of data sets for ML solutions already in the data understanding phase of an implementation. Knowledge about the necessary data cleaning efforts and result qualities...

Purpose: Traffic volume in empty container depots has been highly volatile due to external factors. Forecasting the expected container truck traffic along with having a dynamic module to foresee the future workload plays a critical role in improving the work efficiency. This paper studies the...

We examine the impact of Articial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers' productivity by shortening the...

This paper contributes to the economics of AI by exploring three topics neglected by economists: (i) the notion of a Singularity (and Singleton), (ii) the existential risks that AI may pose to humanity, including that from an extraterrestrial AI in a Dark Forest universe; and (iii) the relevance...

We study how researchers can apply machine learning (ML) methods in finance. We first establish that the two major categories of ML (supervised and unsupervised learning) address fundamentally different problems than traditional econometric approaches. Then, we review the current state of...