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Obwohl Handelsplattformen zunehmend an Bedeutung gewinnen, besteht im deutschsprachigen Raum ein Mangel an umfassenden Marktübersichten. Dadurch fehlt es Verkäufern, potenziellen Plattformbetreibern und Kunden an einer soliden Grundlage für fundierte Entscheidungen. Das ändern wir mit folgendem Beitrag. Erfahren Sie hier das Wichtigste über den rasant wachsenden Markt der Handelsplattformen.
Navigating the unknown
(2024)
Visionary leadership is considered to be one of the most important elements of effective leadership. Among other things, it is related to followers' perceived meaningfulness of their work. However, little is known about whether uncertainty in the workplace affects visionary leadership's effects. Given that uncertainty is rising in many, if not most, workplaces, it is vital to understand whether this development influences the extent to which visionary leadership is associated with followers' perceived meaningfulness. In a two-source, lagged design field study of 258 leader-follower dyads from different settings, we show that uncertainty moderates the relation between visionary leadership and followers' perceived meaningfulness such that this relation is more strongly positive when uncertainty is high, rather than low. Moreover, we show that with increasing uncertainty, visionary leadership is more negatively related to followers' turnover intentions via perceived meaningfulness. This research broadens our understanding of how visionary leadership may be a particularly potent tool in times of increasing uncertainty.
Invisible iterations: how formal and informal organization shape knowledge networks for coordination
(2024)
This study takes a network approach to investigate coordination among knowledge workers as grounded in both formal and informal organization. We first derive hypotheses regarding patterns of knowledge-sharing relationships by which workers pass on and exchange tacit and codified knowledge within and across organizational hierarchies to address the challenges that underpin contemporary knowledge work. We use survey data and apply exponential random graph models to test our hypotheses. We then extend the quantitative network analysis with insights from qualitative interviews and demonstrate that the identified knowledge-sharing patterns are the micro-foundational traces of collective coordination resulting from two underlying coordination mechanisms which we label ‘invisible iterations’ and ‘bringing in the big guns’. These mechanisms and, by extension, the associated knowledge-sharing patterns enable knowledge workers to perform in a setting that is characterized by complexity, uncertainty and ambiguity. Our research contributes to theory on the interplay between formal and informal organization for coordination by showing how self-directed, informal action is supported by the formal organizational hierarchy. In doing so, it also extends understanding of the role that hierarchy plays for knowledge-intensive work. Finally, it establishes the collective need to coordinate work as a previously overlooked driver of knowledge network relationships and network patterns. © 2024 The Authors. Journal of Management Studies published by Society for the Advancement of Management Studies and John Wiley & Sons Ltd.
With the surging reliance on videoconferencing tools, users may find themselves staring at their reflections for hours a day. We refer to this phenomenon as self-referential information (SRI) consumption and examine its consequences and the mechanism behind them. Building on self-awareness research and the strength model of self-control, we argue that SRI consumption heightens the state of self-awareness and thereby depletes participants’ mental resources, eventually undermining virtual meeting (VM) outcomes. Our findings from a European employee sample revealed contrary effects of SRI consumption across speaker vs listener roles. Engagement with self-view is positively associated with self-awareness, which, in turn, is negatively related to satisfaction with VM process, perceived productivity, and enjoyment. Looking at the self while listening to others exhibits adverse direct and indirect (via self-awareness) effects on VM outcomes. However, looking at the self when speaking exhibits positive direct effects on satisfaction with VM process and enjoyment.
Enhancing higher entrepreneurship education: insights from practitioners for curriculum improvement
(2024)
Curricula for higher entrepreneurship education should meet the requirements of both a solid theoretical foundation and a practical orientation. When these curricula are designed by education specialists, entrepreneurs are usually not consulted. To explore practitioners’ curricular recommendations, we conducted 73 semi-structured interviews with entrepreneurs with at least five years of professional experience. We collected 49 items for teaching and learning objectives, 37 for contents, 28 for teaching methods, and 17 for assessment methods. The respondents are convinced that students should acquire solid knowledge in business and management, legal issues, and entrepreneurship. For the latter, only some core aspects are provided. The entrepreneurs put greater emphasis on entrepreneurial skills and attitudes and consider experiential learning designs as most suitable, both in the secure setting of the classroom and in real life. The findings can help reflect on current entrepreneurship curriculum designs.
Enhancing economic efficiency in modular production systems through deep reinforcement learning
(2024)
In times of increasingly complex production processes and volatile customer demands, the production adaptability is crucial for a company's profitability and competitiveness. The ability to cope with rapidly changing customer requirements and unexpected internal and external events guarantees robust and efficient production processes, requiring a dedicated control concept at the shop floor level. Yet in today's practice, conventional control approaches remain in use, which may not keep up with the dynamic behaviour due to their scenario-specific and rigid properties. To address this challenge, deep learning methods were increasingly deployed due to their optimization and scalability properties. However, these approaches were often tested in specific operational applications and focused on technical performance indicators such as order tardiness or total throughput. In this paper, we propose a deep reinforcement learning based production control to optimize combined techno-financial performance measures. Based on pre-defined manufacturing modules that are supplied and operated by multiple agents, positive effects were observed in terms of increased revenue and reduced penalties due to lower throughput times and fewer delayed products. The combined modular and multi-staged approach as well as the distributed decision-making further leverage scalability and transferability to other scenarios.