The modern workplace has been profoundly transformed by the widespread integration of digital technologies, fundamentally changing the way individuals conduct business and interact within their work environments. However, this digital transformation has also created a major problem relevant to both research and practice: the ubiquitous prevalence of work interruptions (e.g., receiving unexpected emails or instant messages while focused on a task). Against this background, we conducted a qualitative study to allow digital business professionals to describe their general perception and management of interruptions. As a result, we validate and refine a category system developed in a previous study on specific interruption types, quantify their outcomes on psychological well-being and work performance, and examine how they are handled, thus filling gaps in the existing literature on interruption perception and management. Overall, this category system can serve as a valuable foundation for future interruption science research.

This study explores the prevalence of hate speech (HS) and sentiment in YouTube video comments concerning the Israel-Palestine conflict by analyzing content from both public and private news sources. The research involved annotating 4983 comments for HS and sentiments (neutral, pro-Israel, and pro-Palestine). Subsequently, machine learning (ML) models were developed, demonstrating robust predictive capabilities with area under the receiver operating characteristic (AUROC) scores ranging from 0.83 to 0.90. These models were applied to the extracted comment sections of YouTube videos from public and private sources, uncovering a higher incidence of HS in public sources 40.4% compared to private sources 31.6%. Sentiment analysis revealed a predominantly neutral stance in both source types, with more pronounced sentiments towards Israel and Palestine observed in public sources. This investigation highlights the dynamic nature of online discourse surrounding the Israel-Palestine conflict and underscores the potential of moderating content in a politically charged environment.

The increasing importance of digital health platforms (DHPs) necessitates the development of a systematic approach to their categorisation and evaluation in order to optimise the integration of DHPs into the healthcare system. The aim of this paper is to develop a taxonomy for structured categorisation and identification of digital health platforms. We develop the taxonomy based on legal, technological and economic aspects and validated it using empirical-to-conceptual and conceptual-to-empirical approaches. By applying the taxonomy to the Apple Health platform, we demonstrate its practicability and potential to identify platform-specific characteristics, which can help with strategic positioning within the healthcare sector. Further research opportunities exist in adapting and extending the taxonomy to account for evolving trends and innovations in the field.

The transition towards renewable energy sources in the energy market has revealed new challenges for power distribution grid operators, including a high demand for skilled workers. At the same time, an aging workforce and a shortage of skilled workers aggravate the issue of filling these vacancies.
To address these challenges, this study proposes using knowledge management (KM) and knowledge management systems (KMS) to retain and transfer critical organizational knowledge.
By storing knowledge in KMS and distributing it among employees, organizations can enhance productivity and encourage innovation, while mitigating the impact of the shortage of workers.
This study follows a design science approach to integrate KMS into existing information system architectures of energy grid operators. Such architectures commonly contain enterprise resource planning and geographic information systems.
Furthermore, the integration of Artificial Intelligence (AI) for generating knowledge is investigated. Such use of generative AI can reduce the expenditures of documenting knowledge in KMS.

Public transport can be a sustainable and efficient way to provide mobility. However, its use is declining while the number of car owners is escalating. Previous research overlooks the dual nature of public transport in rural areas, as it can be both a mobility enabler and disenabler, and the question of how digitalisation can influence this is also not sufficiently considered. This paper attempts to fill this gap through a comprehensive literature review, including the consideration of regional characteristics and system design. For this purpose, 21 papers were analysed and the challenges and opportunities for improving public transport in rural areas were identified. The findings underscore the need for holistic approaches integrating technological, organizational, and societal dimensions to maximize the benefits of rural public transport and address mobility challenges effectively.

In times of increased demand for skilled workers, targeting the right universities and locations for recruitment has become increasingly important, particularly for startups. This paper examines the provision of startup skill profiles by German universities and the migration of such profiles after graduation. In addition to the quantity and concentration of profiles per university, the findings reveal how cities and states retain talent. The results show how universities strengthen the availability of skilled workers in their region. Hotspots such as North Rhine-Westphalia, Bavaria and Berlin also attract the largest share of talent from surrounding areas, while retaining an above-average number of talents. Startups can evaluate different locations for their location choice and recruitment strategy. Local governments and policymakers are made aware of how they are affected by out-migration and whether they can compete with the top startup hotspots in terms of talent retention.