Background On 16 December 2025, under the label “Simplification Omnibus”, the European Commission tabled a legislative proposal (COM (2025) 1030 final) that simultaneously amends various legal acts in the area of food and pesticide law. As regards plant protection products, the proposal pursues four structural interventions. Three operate on the knowledge-input side of the risk-governance system: the conversion from time-limited to open-ended active substance approvals, the freezing of the state of knowledge underlying the active substance approval as the binding standard of review in the subsequent product authorisation procedure, and the introduction of deemed authorisation upon expiry of time limits. A fourth operates on the output side: the extension of grace periods, which allows substances whose approval has been withdrawn on health or environmental grounds to remain on the market for up to three further years. This contribution assesses these measures against primary law. Results Their cumulation structurally eliminates the dynamic updating of scientific knowledge required by the precautionary principle, without the proposal prescribing a functionally equivalent replacement system: the first three measures bar new risk knowledge from entering the assessment, while the extended grace periods prevent the system from acting on risk knowledge it has already confirmed. The proposal thus opens the regulatory loop at both ends. At the same time, the measures fail their own simplification objective: the reactive review system generates more administrative burden in any meaningful application than the application-driven renewal procedure, and deemed authorisation does not relieve administrations either, but compels them to maintain dedicated personnel capacities for keeping deadlines. The measures are therefore already questionable at the suitability stage of proportionality review. Deemed authorisation additionally constitutes a structural rupture with primary law, as it reverses the allocation of the burden of proof in risk authorisation law that the precautionary principle prescribes. Conclusions The contribution shows how the proposal could be developed in a manner compatible with primary law, and where the limits of reformability lie.

Die vorliegende Bachelorarbeit untersucht die Funktion und Effektivität der mietrechtlichen Sozialklausel gemäß §§ 574 ff. BGB. Im Mittelpunkt steht die Forschungsfrage, ob die Sozialklausel in ihrer praktischen Anwendung durch die Gerichte einen effektiven Schutz von Mietern vor sozial unzumutbaren Kündigungsfolgen gewährleistet. Dabei wird insbesondere das Spannungsverhältnis zwischen dem Eigentumsrecht des Vermieters aus Art. 14 GG und dem sozialen Bestandsschutz des Mieters betrachtet. Die Untersuchung verbindet eine rechtsdogmatische Analyse mit einer empirischen Auswertung von 86 instanzgerichtlichen Entscheidungen seit der Mietrechtsreform 2001. Neben der historischen Entwicklung und dem verfassungsrechtlichen Rahmen werden insbesondere die Rechtsprechung des Bundesgerichtshofs sowie die Anforderungen an die Darlegung und den Nachweis von Härtegründen untersucht. Der empirische Schwerpunkt liegt auf Eigenbedarfskündigungen und der gerichtlichen Berücksichtigung struktureller, sozialer und medizinischer Härtegründe. Die Ergebnisse zeigen, dass in 46 von 86 untersuchten Entscheidungen eine mieterfreundliche Entscheidung erging. Besonders hohe Erfolgsaussichten bestanden bei medizinischen Härtegründen: 21 von 24 entsprechenden Fällen wurden zugunsten der Mieter entschieden. Gleichzeitig scheiterten Härteeinwände häufig an einer unzureichenden Substantiierung oder Beweisführung. Die Untersuchung zeigt damit, dass die mietrechtliche Sozialklausel grundsätzlich einen wirksamen Schutzmechanismus darstellt, ihre praktische Effektivität jedoch maßgeblich von der individuellen Darlegung und Beweisbarkeit der geltend gemachten Härte abhängt. Insgesamt gewährleistet sie einen relevanten, jedoch nicht uneingeschränkten Schutz vor sozial unzumutbaren Kündigungsfolgen. Schlüsselwörter: Mietrechtliche Sozialklausel; §§ 574 ff. BGB; Mieterschutz; Kündigung; Eigenbedarfskündigung; Härtegrund; Härtefall; soziale Härte; medizinische Härte; Art. 14 GG; Eigentumsgarantie; Bundesgerichtshof; BGH-Rechtsprechung; Kündigungsfolgen; Mieterrecht

AI is fundamentally transforming all areas of our lives, including research and education. It opens new opportunities and unfolds a multitude of critical discussions. Among others, the discussion about future trends in research and education is lively and diverse, ranging from optimistic sentiments about “AI takes it all” to pessimistic tones about dehumanization and the degradation of thinking capabilities. We do not know to what extent AI will come to dominate in the future. However, thinking about research and education in an AI-augmented world might be useful regardless of how much AI will be in our lives in the future. In this note, I try to take a balanced position and provide my opinion on how research and education in general, and operations management in particular, could evolve in the AI era, considering both chances and risks. As one of the outcomes of this viewpoint note, a framework is proposed, featuring three main elements that education and research should be composed of, i.e., human knowledge base (i.e., what we know without asking AI), AI-augmented thinking and learning, and human-AI collaboration in solving complex problems. I also discuss how journal editorial and review practices, universities and their (operations management) course curricula, and research funding assessments could evolve over time, concluding that the academic profession would change, and not necessarily for the worse.

In this paper, we present a conceptual design for a decision-support system to address tariff-induced uncertainty and disruptions. The system is comprised of predictive (simulation) and prescriptive (optimization) supply chain analytics supplemented by an LLM module for real-time disruption detection. We illustrate applications of the system developed in AnyLogistix supply chain optimization and simulation software and offer generalized mathematical formulations. The experimental part includes several supply chain stress tests under different tariff scenarios, conducted using discrete-event simulation, and recommendations for proactive supply chain reconfiguration via network optimization. This study has both theoretical contributions and practical implications. For the first time, we conceptualize a decision-support system specifically tailored to the specifics of tariff-induced uncertainty. We also show how the decision-support system proposed can be extended toward a digital twin. Our models can be used immediately in practice for stress testing supply chain resilience and for reconfiguration in response to tariff shocks.