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Purpose – This study sets out to examine the mediating role of quiet quitting in the relationship between various workplace antecedents and turnover intention, with a specific focus on generational differences across GenX, GenY, and GenZ.
Aims(s) – The primary aim is to identify the antecedents that show significant indirect generation-specific effects on turnover intention via quiet quitting. Design/methodology/approach – Utilizing a sample of 2,193 urban and suburban employees from Berlin, Germany, this study tested a mediation model featuring five independent variables linked to quiet quitting, with turnover intention as the outcome variable. The analysis employed Cronbach’s alpha, confirmatory factor analysis, multicollinearity checks, and multiple-mediation regression techniques.
Findings – The results reveal that quiet quitting partially mediated the relationship between dissatisfaction and turnover intention for GenY, as well as the relationship between negative extra-role behavior and cynicism/depersonalization for GenZ. Additionally, negative work-life balance showed partial mediation across all three generations—GenX, GenY, and GenZ. Full mediation effects were observed specifically in GenZ for both negative extra-role behavior and cynicism/depersonalization. No significant mediating effect of quiet quitting was found for disengagement. Limitations of the study – The sample is limited to Berlin and its suburbs, with no comparative data from other regions. The generational groups are represented by moderately sized subsamples. Additionally, after conducting reliability analysis and confirmatory factor analysis (CFA), most scales were reduced to just two or three items.
Originality/value – This study positions quiet quitting as a mediating factor within a network of related variables and is among the first to examine how these mediation effects differ across GenX, GenY, and GenZ.
Die bundesdeutschen Kommunen erlebten im Jahr 2024 einen beispiellosen Absturz ihrer Haushaltslagen. Dieser Beitrag geht den Ursachen nach und nimmt insbesondere die Wirkungen von Konjunktur, Inflation und Fluchtmigration in den Blick. Die Analyse zeigt, dass die Haushaltskrise auf einem starken Anstieg der Ausgaben beruht. Die Personalausgaben steigen durch Stellenzuwächse und hohe Tarifabschlüsse infolge der Inflation. Die Sachausgaben werden direkt durch Inflation erfasst. Gleiches gilt für die Investitionen, womit sich deren Anstieg relativiert. In Bezug auf die Sozialausgaben liegen die Ursachen des Anstieges in politischen Ausweitungen der Leistungsansprüche sowie der Demografie. Effekte der Fluchtmigration bestehen in der Breite der Aufgaben, sind jedoch meist nicht exakt messbar. Die schwache Konjunktur ist bisher noch nicht ausgabenwirksam. Es zeigt sich, dass diese Haushaltskrise nicht vorübergehender Natur ist, sondern hinsichtlich der Ursachen fortbestehen wird. In Reaktion darauf werden die Kommunen ihre Investitionen kürzen. Mittelfristig drohen sie handlungsunfähig zu werden.
Diese Masterarbeit beleuchtet die Entwicklung eines dialogbasierten Recommender-Systems, das Studierenden die Auswahl und Nutzung von Fachdatenbanken erleichtern soll. Der Fokus liegt auf der Integration von Large Language Models (LLMs) und der Retrieval-Augmented Generation (RAG)-Technik, um kontextbezogene Antworten aus einer Wissensdatenbank zu generieren. Diese Wissensdatenbank wurde aus den Metadaten des Bibliotheks-Management-Tools erzeugt. Die Arbeit analysiert die Anforderungen an einen solchen Chatbot hinsichtlich organisatorischer und rechtlicher Vorgaben, wie z.B. Datenschutz, sowie die Anforderungen an die technische Infrastruktur und die Auswahl geeigneter LLMs. Zudem wird ein modellhafter Workflow skizziert, der als Grundlage für ähnliche Projekte dienen kann. Die Ergebnisse zeigen, dass durch die Kombination von LLMs und RAG-Technik durchaus ein lokaler Chatbot erstellt werden kann, der Benutzer*innen bei der Suche nach speziellen Bibliotheksressourcen unterstützen kann.
Indonesia has enjoyed impressive economic growth since the early 2000s and consequently attracted significant business interest from western companies. Yet, the Indonesian business context has also been notoriously impacted by corruption, which presents a serious challenge for international business negotiations. Interestingly, in scholarly research little is known about the indigenous management practices within the Indonesian context. This study therefore investigates indigenous management practices during international business negotiations taking place in the emerging market of Indonesia, that may determine the success or failure of multinational corporations’ negotiations. We conduct an inductive analysis of rich and context-specific data generated through 55 in-depth interviews of Indonesian and non-Indonesian managers. We discover: (1) the importance of perantara as a third-party agent, specific to Indonesia, that operates as a backchannel conduit for communication between parties and is essential for progressing to the face-to-face negotiation stage; and (2) the unique relationship-building process essential for business negotiations in Indonesia, which moves from task orientation to relationship-building orientation. To the best of our knowledge, our study is one of the first to tackle such specific indigenous management behaviours during international business negotiation in Indonesia from a context-specific insider’s perspective. This study provides useful insights for managers of foreign multinational corporations on how to manage certain indigenous Indonesian management behaviours if they are to achieve successful investment outcomes.
Those who suffer from aphasia benefit from digital speech and language therapy solutions, and automatic speech recognition (ASR) has been already used for giving feedback on the correctness of the answers in naming exercises. AphaDIGITAL application is to provide German-speaking users with detailed feedback on phonemic/phonetic and semantic errors, based on automatic speech and language processing. For this purpose, open-source ASR solutions for German were evaluated on different corpora of atypical speech, including two small datasets with aphasic speech samples. Character error rate, the number of precisely recognized items and empty outputs served as evaluation metrics. The four selected models are generally robust to the deteriorated condition of speech and audio quality and consistently outperform commercial models in atypical speech recognition. Applying error acceptance threshold, additional use of phonemic error rate, and other valuable insights for ASR implementation in aphaDIGITAL are discussed.
Dieses Arbeitspapier gibt einen umfassenden Überblick über aktuelle Normen und Standards, die für das Projektmanagement (PM) von Bedeutung sind. Hierfür kamen Methoden der Dokumentenanalyse, der systematischen Literaturanalyse und der qualitativen Inhaltsanalyse zum Einsatz. Als relevante Normungsorganisationen werden die International Organization for Standardization (ISO), das Deutsche Institut für Normung (DIN), das US-amerikanische American National Standards Institute (ANSI) und The British Standards Institution (BSI) berücksichtigt. Bei den Standards werden solche Organisationen als relevant erachtet, die in der Lage sind, den von ihnen publizierten Standard einem breiten, im Projektmanagement tätigen Adressatenkreis publik zu machen, Dienstleistungen, wie z. B. Schulungen, anzubieten, und eine Weiterentwicklung des Standards sicherzustellen. Insgesamt werden 37 PM-Normen und 54 PM-Standards, die von 29 Trägerorganisationen publiziert werden, beschrieben. Die Darstellung umfasst beispielsweise die Normenreihen DIN 6990x und ISO 215xx. Als Projektmanagement-Standards werden neben den bekannten PM-Standards, wie der IPMA Individual Competence Baseline® (IPMA ICB®), PRINCE2®, PM2 oder dem PMBOK® Guide, auch neuere PM-Standards, die sich z. B. der Agilität oder der Nachhaltigkeit im Projektmanagement widmen, behandelt. Auch Standards für Programm- und Portfoliomanagement sowie Standards für die Prüfung von Projekten finden Berücksichtigung. Jede Norm und jeder Standard werden einzeln systematisch dargestellt. Die jeweilige Beschreibung enthält eine prägnante Inhaltsangabe, den formellen Status der Norm bzw. des Standards und Links für die eigene Recherche. Insofern soll dieses Arbeitspapier nicht nur eine aktuelle, systematische Zusammenstellung bieten, sondern es stellt auch eine Hilfestellung für ein schnelles Orientieren und Nachschlagen dar. Hierfür wurden die PM-Normen und -Standards verschiedenen Kategorien zugeordnet, die ihre inhaltliche Ausrichtung signalisieren.
Diese Studie analysiert, ob Gesichtsausdrücke in generierten Bildern genauso wahrgenommen werden wie in realen Bildern. Dabei werden die Wahrnehmung der Emotionsintensität und Sympathie, die Fähigkeit zur Emotionserkennung sowie die Unterscheidung zwischen echten und generierten Bildern untersucht. Zur Beantwortung dieser Fragen wurde eine Online-Umfrage mit mehr als 200 Teilnehmern durchgeführt. Die Ergebnisse zeigen geringfügige bis moderate Unterschiede in der Wahrnehmung zwischen generierten und realen Bildern, allerdings wird auch deutlich, dass die Unterscheidung zwischen beiden zunehmend schwieriger wird.
The visibility of an endangered language online plays a crucial role in language revitalisation. The internet offers a new domain for using minority languages, especially for speakers living outside the language communities. This article investigates Karelian language visibility on X, formerly known as Twitter, and describes the first corresponding data collection using language-related keywords and hashtags. In total, 2,625 entries written fully or partially in Livvi, South and Viena Karelian were scraped with Postman API. The visibility of Karelian on Twitter (X) has been increasing considerably in the past few years, with Livvi-Karelian being the most prominent dialect. Automatic language detection was tested on such data for Karelian for the first time, and allows the identification of Livvi-Karelian (or a mix of dialects that include Livvi-Karelian) with 99.7% sensitivity, and South Karelian and Viena Karelian as Livvi-Karelian with 90% and 73.8% sensitivity, respectively. The entries were also analysed thematically, and 10 major topics were identified. Since the data was collected using keywords and hashtags related to the Karelian language itself, most of the entries are related to the language and vocabulary in sense of translation or language learning. Language status and policy is another important topic identified in the data. Although language-related topics are the most popular, there are a substantial number of entries on eight further topics. Excluding citations from religious texts and media headlines, 751 Twitter (X) entries could be used for linguistic and sociological research. Further data collection considerations are also discussed.
A review of the literature on the application of artificial intelligence (AI) in the recruitment and selection process (RSP) was conducted, but no relevant studies were identified. While several reviews have focussed on AI in human resource management in general, none of these have examined the RSP in detail or employed an AI taxonomy for clustering. Consequently, we applied an AI taxonomy identified in the literature with the aim to identify the stages of the RSP in the focus of research and the algorithms mostly used. We conducted a systematic literature review underpinned by a concept matrix, complemented by a computational literature review (CLR), that employed natural language processing (NLP). The initial 4,579 studies were sourced from three databases and narrowed down to a total of 502. Our major findings indicate that the majority of studies were categorised under the stages “assessment & selection” and “processing incoming applications” in the RSP. The predominant algorithms in use pertain to the field of NLP and machine learning. The CLR emphasised the significance of ethics in AI research. While our study has expanded the general AI taxonomy by incorporating an ethical perspective and is one of the studies with the most articles used to reflect this topic, it is solely focussing on describing the past. Nevertheless, this article helps to align research on exploring and testing alternative approaches with those most frequently used.
Addressing wicked problems of our society demands fundamental changes in the way we live. Universities play a pivotal role in this process through the creation and dissemination of knowledge, engaging broad sectors of society to improve understanding and to inspire action. However, universities face barriers in fulfilling their role in addressing complex societal challenges such as climate change. This contribution explores the potential of the arts to foster public engagement and stimulate responsible pathways of research at universities within this context. Using an integrative literature review, the paper provides an overview of conceptual contributions aimed at understanding different modes of the interplay between the arts, science, and society, or, more specifically, of integrating the arts into the university’s third mission. The overview is organized around three pillars: (i) arts in knowledge creation, (ii) arts in the communication of scientific research, and (iii) arts in the alignment of research with societal needs. Within each pillar, specific modes of interplay between the arts, science, and society are identified and exemplified with selected climate-related artworks: i) artistic research, arts-based research, arts-science collaboration, ii) arts-based science communication and iii) arts-based responsible research and innovation. The examples hihlight resources, processes and activities enabling different modes of interplay between arts, science and society. The value of defining such modes of interplay is their use as conceptual tools for deriving arts-based strategies for university’s third mission. They can help understanding the integrative potential of arts in third mission activities around diverse pillars and relevant conditions for impact assessment.

