This study investigates the dual impact of Generative AI (GenAI) on business value in knowledge work by examining value co-creation and co-destruction, focusing on operational excellence. Despite the growing adoption of GenAI tools, a significant gap remains in understanding how their generative capabilities simultaneously enhance and constrain business value in real-world contexts. Prior research has predominantly focused on GenAI's technical potential, overlooking the complex interplay between its enabling and inhibiting effects on operational performance. To address this gap, we conducted a comprehensive investigation combining qualitative insights from 15 industry experts across diverse sectors and a quantitative deep dive into key operational metrics derived from software development teams’ GitHub repositories. Our findings reveal that while GenAI can enhance operational excellence by automating repetitive tasks, reducing workload, and fostering innovative problem-solving, it can also introduce risks such as productivity variability, erosion of contextual human judgment, and over-reliance on AI-driven processes. Furthermore, we identify inconsistencies in value creation outcomes across different teams, emphasizing the importance of tailored integration strategies and continuous oversight. By contextualizing these insights within value co-creation, co-destruction, and the value discipline lens, we offer actionable recommendations for practitioners aiming to achieve sustainable GenAI integration. Ultimately, this study provides a structured approach to evaluate GenAI’s dual impact. This study offers academics and practitioners a framework for balancing its co-creative potential with its inherent risks, particularly in knowledge-intensive environments.

Just like calcium, magnesium, and iron, water is vital for life on our planet. Alarming evidence indicates that water is becoming scarce. In this critical situation, the management of hydric systems turns out to be a bottleneck. Established modes focus on regulation through laws and rulings. This paper offers a ethodological contribution to improving the governance of River Basin Organizations (RBOs): a cybernetic model is introduced for the diagnosis and (re-)design of water governance, which is new in this context: the iable System Model (VSM). This model embodies both a theory and a methodology, incorporating a heuristic cybernetic framework. The theory it provides is unique in its claim to specify the necessary and sufficient preconditions for the viability of any social system. It gives access to the deep structures that ensure the viability of social, and thereby socio-ecological and socio-technical systems. The VSM also provides a methodology that is highly beneficial in environmental, social, and economic terms. Using the VSM in the field of water governance is unorthodox and challenging. It has the potential to balance the need and supply of water, and even to reframe the system-in-focus, ensuring its viability and sustainability. The theoretical claim of the model is underpinned by an extensive case study from the Tocantins-Araguaia Hydrographic Region in Brazil—the largest hydrographic basin completely within Brazil. The insights gained from this account allow for cautious generalization and enable impactful applications.

Management in systemic terms means to cope with complexity. Ross Ashby’s Law of Requisite Variety shows the way, - to maintain the varieties of interacting systems in balance. To denote that process, we use the cybernetic concept of «Variety Engineering», which we also formalize. It refers to processes of mutual complexity amplification and attenuation by interacting agents. The purpose of this contribution is to explore ways of coping with complexity by means of Variety Engineering. The abstract concepts are illustrated by examples from ecological, social, and economic contexts. The cases in point will be used to demonstrate how complexity can be managed, to foster sustainability.

Payment mechanisms are important factors for the use and diffusion of technological innovation. Nevertheless, there is a lack of knowledge and empirical evidence about the payment instruments and mechanisms used for technological innovation in the inpatient sector across European health care systems. Given this background, this articles discusses the relationships between DRG-based payment systems and technological innovation. Moreover, it analyses available short-term payment instruments for technological innovation and their application across eleven European countries. The article also scrutinizes how technological innovations are integrated into DRG-based payment systems in the long run. We fi nd that long term mechanisms differ with respect to i) the frequency of system updates, and ii) the time-lag to the data used for these updates. Our analysis suggests that one can differentiate between different kinds of short-term payment instruments: on the one hand some countries apply separate payments outside the core scope of DRG-based payment systems. On the other hand countries provide additional payments and cost-outlier funding that operates within the framework or at the margin of DRG-based payment systems. Overall, our analysis suggests that payment approaches in the context of DRG-based pay-ment systems differ substantially across European health care systems. German as well as other European policy makers should pay more attention to the diversity of payment approaches across European health care systems to inform their policy making.