The working environment is constantly changing and companies face the challenge of adapting to new and constantly changing customer requirements. Employees are faced with the challenge of identifying and learning new, helpful technologies and using them in order to achieve efficiency gains and increase productivity. This article addresses the three technologies Artificial Intelligence, Robotic Process Automation and Virtual Reality, which will play an important role in the future of work and will influence the Work Environment 4.0. Artificial Intelligence and Robotic Process Automation relieve employees of repetitive and manual tasks which thus accelerate and simplify business processes. Virtual Reality offers employees new opportunities to collaborate in virtual environments. Instead of performing routine tasks, employees will increasingly promote the use of such technologies in future and orchestrate their application. In addition, it is important for employees to continuously look for new use cases within their own organization and to collaborate with external partners. The article aims to describe the opportunities that arise from the application of the technologies and to explain their effects on the Work Environment 4.0 and the employee.

The automotive industry is undergoing a profound transformation driven by technological innovations, such as electrification, autonomous driving systems, digitalization, and the shift toward mobility services. This transformation is further intensified by new competition from the IT sector, industrial policy objectives, particularly from China, and the increasing automation and connectivity of manufacturing processes. In addition, environmental regulations, evolving consumer preferences, and advancements in artificial intelligence (AI) play a crucial role in shaping the industry’s future. This study aims to identify and analyze the key technological drivers contributing to the transformation of the automotive sector. Using a systematic literature review based on the approach outlined by vom Brocke et al., a structured and reproducible analysis of the relevant literature is conducted. The findings indicate that technological drivers, such as connectivity, autonomous driving, electrification, and digitalization are crucial to this transformation. Furthermore, supporting technologies such as AI, cloud computing, and big data analytics are critical enablers of this transformation. A deep understanding of these drivers is essential for industry stakeholders, policymakers, and researchers to anticipate future developments, address emerging challenges and develop effective strategies for sustainable and competitive mobility solutions. This study contributes to the ongoing discourse on transformation and its implications for the future of the automotive industry.

This paper focuses on quantifying the economic and financial viability of NB-IoT and LoRaWAN technologies, two low-power wide-area network (LPWAN) technologies with unique characteristics that make them suitable for IoT applications. The purpose of this study is to propose a “pragmatic” artifact for performing life cycle cost analysis and demonstrate its application to these technologies. The methodology uses pragmatic computational tools to facilitate the analysis and considers all relevant economic and financial factors, such as operating costs, equipment costs, and revenue potential. The main finding of this study is that Narrow Band-Internet of Things (NB-IoT) and Long Range Wide Area Network (LoRaWAN) technologies have different cost structures and revenue potentials, which may affect their economic and financial viability for different IoT applications. Ultimately, the study concludes that a comprehensive life cycle cost analysis is critical to making informed decisions about technology adoption, and that the proposed methodology can be applied to other IoT technologies to gain insight into their economic and financial viability.

The transition to battery electric vehicles (BEVs) poses significant challenges for automotive suppliers, particularly in the Northern Black Forest Region, Germany’s largest industrial area. This study examines the risk of falling into the commodity trap and the impact of platform economics on these suppliers. A VUCA (volatility, uncertainty, complexity, ambiguity) analysis is used to assess the consequences of the open platform approach promoted by the Mobility in Harmony (MIH) Consortium. The methodology is based on a comprehensive literature review on commodity traps and platform economies, as well as an analysis of the MIH Consortium’s strategies for standardizing BEV components. The results show that while the MIH Consortium’s modularization and standardization efforts can reduce costs and facilitate mass production, they also intensify competition and limit differentiation, threatening the profit margins of smaller suppliers. The study highlights the importance of strategic positioning and innovation to counter these risks. It concludes with recommendations on how automotive suppliers can adapt to the evolving environment and be agile in responding to new technological standards and market dynamics.

This research paper examines the risks posed by the MIH EV Open platform to German automotive suppliers, in particular, the risk of commoditization and falling into a commodity trap. The term commodity trap describes a situation in which companies dealing with standardized products or services face intense price and margin pressure and struggle to differentiate themselves from competitors. The MIH EV Open platform, established by Foxconn, also known as Hon Hai Precision Industry Co. Ltd., headquartered in Tucheng, Taipei, Taiwan, aims to create a collaborative platform for the comprehensive development of key software, hardware components, and services in the electric vehicle (EV) industry. It unites over 2700 companies from more than 70 countries and fosters collaboration to accelerate the development and market entry of new EV products. This paper analyzes the MIH EV Open business ecosystem model and assesses the strengths and weaknesses of German suppliers in addressing these challenges. This study highlights strategic approaches, including innovation, portfolio adaptation, customer relationships, and sustainability practices, that can enable German suppliers to mitigate commodity trap risks. The findings underscore the importance of proactive, segment-specific strategies amidst the transformation of the automotive industry. Key insights are provided on the potential impact of open platform ecosystems and recommendations for German automotive suppliers to maintain competitiveness. This research fills a gap in the literature by examining the commoditization risks posed by the MIH EV Open platform for German automotive suppliers. Unlike previous studies that focus on traditional market structures, this study explores the novel dynamics introduced by platform ecosystems and provides strategic insights to mitigate these risks.