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Auflistung nach Autor:in "Laumer, Sven"

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  • Zeitschriftenartikel
    A Dark Side of Telework: A Social Comparison-Based Study from the Perspective of Office Workers
    (Business & Information Systems Engineering: Vol. 64, No. 6, 2022) Maier, Christian; Laumer, Sven; Weitzel, Tim
    Telework became a necessary work arrangement during the global COVID-19 pandemic. However, practical evidence even before the pandemic also suggests that telework can adversely affect teleworkers’ colleagues working in the office. Those regular office workers may experience negative emotions such as envy which, in turn, can impact work performance and turnover intention. In order to assess the adverse effects of telework on regular office workers, the study applies social comparison theory and suggests telework disparity as a new theoretical concept. From the perspective of regular office workers, perceived telework disparity is the extent to which they compare their office working situation with their colleagues’ teleworking situation and conclude that their teleworking colleagues are slightly better off than themselves. Based on social comparison theory, a model of how perceived disparity associated with telework causes negative emotions and adverse behaviors among regular office workers was developed. The data were collected in one organization with telework arrangements (N = 269). The results show that perceived telework disparity from the perspective of regular office workers increases their feelings of envy toward teleworkers and their job dissatisfaction, which is associated with higher turnover intentions and worse job performance. This study contributes to telework research by revealing a dark side of telework by conceptualizing telework disparity and its negative consequences for employees and organizations. For practice, the paper recommends making telework practices and policies as transparent as possible to realize the maximum benefits of telework.
  • Zeitschriftenartikel
    Algorithmic Accountability
    (Business & Information Systems Engineering: Vol. 65, No. 6, 2023) Horneber, David; Laumer, Sven
  • Zeitschriftenartikel
    Consequences of Enterprise Social Media Network Positions for Employees
    (Business & Information Systems Engineering: Vol. 65, No. 4, 2023) Schötteler, Sebastian; Laumer, Sven; Schuhbauer, Heidi
    Employees often use enterprise social media (ESM) for communication, collaboration, and knowledge sharing, leading to ESM networks–that is, social networks of interrelated employees based on ESM. Many organizations possess ESM networks, and there is increasing research on their consequences for employees depending on how these employees are positioned in such networks. ESM network research is complex and consists of various interrelated dimensions. However, a synthesis of the abovementioned studies is lacking. Therefore, the current body of knowledge may obfuscate how the different dimensions interrelate, impeding a more holistic understanding of the consequences that employees may experience depending on their network positions. Moreover, there is little understanding of which research topics in this area have been addressed to date and where further research is needed. This paper addresses these gaps by means of a literature review and research agenda that synthesizes past studies. The results emphasize that whether ESM are beneficial for and exert a positive influence on employees largely depends on the employees’ positions in the underlying networks.
  • Zeitschriftenartikel
    E-Assessment
    (Wirtschaftsinformatik: Vol. 51, No. 3, 2009) Laumer, Sven; Stetten, Alexander; Eckhardt, Andreas
  • Zeitschriftenartikel
    Enterprise-Content-Management
    (Wirtschaftsinformatik: Vol. 55, No. 6, 2013) Laumer, Sven; Beimborn, Daniel; Maier, Christian; Weinert, Christoph
  • Workshopbeitrag
    Rejection of Mobile AI-enabled Health Technologies: First Results from an Interview-based Study
    (Mensch und Computer 2024 - Workshopband, 2024) Laumer, Sven; Horneber, David
    Overweight and obesity are common health problems. To address these problems, mobile health technologies based on artificial intelligence (AI) have emerged. These technologies aim to encourage healthy behaviors by helping individuals monitor their exercise and dietary behavior and providing personalized recommendations to support their weight loss. Despite their potential, research has shown that users often abandon these apps prematurely. To address this, our research-in-progress investigates user resistance during the trial phase of mobile health AI-based technology adoption. We propose several factors that explain trial-period rejection, occurring when individuals either fully embrace or reject the technology. This rejection can manifest at the service, digital, or device level. By understanding these sources of resistance, we can enhance the effectiveness of mobile AI-enabled health technologies.