A technical demonstration of remote train operations using 5G mobile communications

The 5G-Reallabor in Braunschweig-Wolfsburg project has demonstrated the technical feasibility of Remote Train Operation (RTO) using 5G mobile communications with special consideration for any human-factor user requirements for the RTO workplace. During the demonstration, a rail vehicle was remotely controlled in two operating scenarios involving remote-controlled shunting and remote-controlled driving for the purpose of clearing an open track on infrastructure in Schlettau (Saxony, Germany) from an RTO workplace situated at the German Aerospace Center (DLR) in Braunschweig

An Agenda for Open Science in Communication

In the last 10 years, many canonical findings in the social sciences appear unreliable. This so-called “replication crisis” has spurred calls for open science practices, which aim to increase the reproducibility, replicability, and generalizability of findings. Communication research is subject to many of the same challenges that have caused low replicability in other fields. As a result, we propose an agenda for adopting open science practices in Communication, which includes the following seven suggestions: (1) publish materials, data, and code; (2) preregister studies and submit registered reports; (3) conduct replications; (4) collaborate; (5) foster open science skills; (6) implement Transparency and Openness Promotion Guidelines; and (7) incentivize open science practices. Although in our agenda we focus mostly on quantitative research, we also reflect on open science practices relevant to qualitative research. We conclude by discussing potential objections and concerns associated with open science practices

A Network Perspective in Supply Chain Risk Management

Classical approaches in the field of supply chain risk management (SCRM) consider supply chains as linear, as the term itself indicates (Hearnshaw and Wilson, 2013). However, modern supply chains are by no means linear—they form complex interconnected networks (e.g., Hearnshaw and Wilson (2013)). This increased complexity is induced by trends such as globalization, increasing product complexity and shorter lead times (Ghadge et al., 2013, Harland et al., 2003). Clearly, new methods for supply chain management are needed, especially those that consider the complexity of today’s supply chains. In this respect, the network structure of supply chains also needs to be considered. For example, studies find that the supply network structure is directly related to resilience, which is the key to effective SCRM (Kim et al., 2015). Research has introduced network theoretical approaches to supply chain management (e.g., Galaskiewicz (2011), Borgatti and Li (2009)). This cumulative dissertation joins the effort by addressing the research field of network theory in the SCRM context. This dissertation contributes to the domain, by first providing a systematic literature review that structures methods for mitigating disruptions in complex supply chains – or to be precise supply networks – and outlines an agenda for further research in the field. Next, in the second paper, it contributes a qualitative model that helps to understand the mechanisms of risks in complex supply chain networks. The same model is the basis for two quantitative studies conveyed in the third and fourth papers that investigate how centrality measures can be used to identify critical suppliers. Finally, the fifth paper conveys a study which directly contributes to practice by developing a supply chain mapping framework as a basis for systematic, effective, and efficient SCRM in complex supply chain networks

A FORMATION MODEL FOR SUPPLY NETWORKS: A FUNDAMENT FOR INVESTIGATIONS OF COMPLEX SUPPLY NETWORKS

Companies today are sourcing products from complex networks. Managing and overseeing these networks is challenging and requires methods including network theoretical considera-tions. Developing these methods demands an underlying model that describes the supply net-work structure and structural data, ideally representative samples. However, large-scale data of real supply network structures is rare, which restricts research in this field. This paper presents a formation model that generates supply networks from a focal company’s perspective. By con-ducting this formation process, exemplary networks are derived and compared to the structural patterns revealed by rare studies investigating real supply networks. The generated networks close the gap of non-available empirical data of large-scale supply networks. The formation is based upon a widely accepted concept of supplier selection. Necessary input parameters are a structured bill of materials. Further details, like the number of competitors, are modelled using a probability distribution. This approach makes it possible for further research to investigate more advanced methods for supporting the management of supply processes. Additionally, using this framework for generating large-scale supply networks makes it possible to acquire a more de-tailed insight into supply network structure