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An important aspect of achieving global climate neutrality and food security is transforming our food system. To support the goal, Germany has set a national target of reaching a 30% share in organic farming. When looking at the transformation process from conventional to organic farming, it becomes apparent that measures need to be taken to reach the anticipated goal. Using Design Science Research, we model and analyze the as-is farm-to-fork value chain of public out-of-home-eaten meals to identify the central barriers and drivers of organic transformation. From the insights gained in the modeling process, we derive a digital platform model that addresses the current issues. We propose a digitally supported value network instead of a hierarchical value chain to share the co-design opportunities for different stakeholders more equally. We then elaborate on the potential to overcome the barriers to organic transformation with the network-based platform. To specify the main functionalities of the digital platform architecture, we map user requirements with the proposed to-be value network. The results further emphasize the need for a change in the current value chain perspective. We conclusively propose to further develop existing approaches under consideration of our identified requirements and the overall sustainability goal, rather than focusing solely on individual dimensions or metrics.
In the following microchapter, the principle of recovery refers to waste as a source of energy. First, the role of waste management in the context of a circular economy transition is described with cross-sectoral impacts and the interconnectedness of waste treatment pathways with waste hierarchy stages and emissions reporting sectors. Then, circular economy policy frameworks integrated into existing management approaches of the EU member states are introduced, exemplifying policy instruments on a regional level, national level and EU-wide, ranging from legislation over economic incentives to voluntary tools. By understanding the specific sources of emissions and their allocation to different sectors, policymakers can better target interventions and initiatives to mitigate the environmental impact of waste. Finally, the Kalundborg Symbiosis is briefly introduced as a well-known example of an innovative waste recovery model. Successful industrial symbiosis relies on proactive collaboration, innovative solutions and supportive policies.
With rapidly increasing demands for sustainable products, the principle of refurbish plays a vital role as one building block of sustainable supply chain management. It refers to the professional general overhaul of products for reuse to extract their maximum value. This microchapter shows the immense potential for saving CO2, water and e-waste along the entire value chain when using refurbed products. In addition, the refurbishing process and the most important trends in the market are presented. A case study from Royal Philips, a global leader in health technology, illustrates which actions are effective when educating customers to adopt sustainable behaviour by purchasing refurbished products. The "Better Than New" campaign to create awareness for Philips’ refurbished products serves as an example.
The principle of recycling encompasses the transformation of waste materials into reusable products or materials, while excluding energy recovery and the use of waste as a fuel. In this microchapter, recycling definitions are introduced, as well as the targets for the reduction of waste generation and recycling rates in the Waste Framework Directive (WFD) of the European Union. Then, recycling measures from actors along the value chain illustrate that collaboration among stakeholders is crucial in creating robust and interconnected recycling systems that maximise resource recovery and minimise waste. Finally, the potential of new technologies along the entire recycling process is observed. A case study from AMP showcases systems that leverage machine learning to identify materials based on visual input, allowing for more effective separation of waste when combined with traditional sorting systems and robotics.
The rethink principle emphasises the importance of creating a continuous cycle and the necessity of circular economy-oriented innovations. It is interconnected to other R-principles, especially refuse and reduce. In this microchapter, the question of how companies can rethink their products/services, business models and ecosystems through sustainability-oriented and circular economy-oriented business model innovation (BMI) is addressed. A card-based tool as a method to explore the circularity potential is introduced. Then, sufficiency-based approaches are outlined, as sufficient consumption patterns rely on business offerings that enable changes - to rethink business in an advanced way. The example of the outdoor apparel and gear company VAUDE illustrates sustainability strategies based on sufficiency.
Circularity is one of the most promising innovative business models for tackling the challenges posed by climate protection, resource conservation and biodiversity conservation. Circularity requires changed business structures; therefore, it is necessary to adapt existing approaches and reconcile economic and ecological interests. By focusing on the importance of horizontal integration and cross-company cooperation, this book offers valuable insights to help companies generate cross-industry synergy and symbiosis effects and secure competitive advantages along sustainable supply chains. The emphasis is on an expanded understanding of the various R principles, and on theoretical and practical application examples that help to prepare corporate business models for the ecological and social challenges of global supply chains.
Given its scope, the book represents an indispensable guide for companies worldwide that want to contribute to sustainable development by adopting circular business models. It analyses the drivers and challenges of implementing these models and presents concepts and insights from pioneering companies in the circular economy, providing a global perspective for managers and researchers alike.
This book comprises a collection of contributions on circular economy in sustainable supply chains. The chapters offer a global perspective on challenges, concepts and implementation cases. The distinguished authors of the chapters, hailing from different locations across the world, bring diverse perspectives and research methods to clarify specific issues related to the integration of circular economy in supply chains across various industries. The contributions are organised into three parts. "Part I: The R-Principles of Circular Economy" features microchapters exploring the foundational principles of the circular economy, encapsulated by the R-principles. "Part II: Theoretical Perspectives of Circular Economy in Global Supply Chains" includes contributions that discuss theoretical issues, providing a robust analytical framework. Finally, "Part III: Practical Implementations of Circular Economy in Global Supply Chains" highlights case studies from various industries and regions, illustrating real-world applications and successes.
Jüngste Fortschritte in der Künstlichen Intelligenz (KI) und der Erweiterten Realität (englisch „extended reality“ [XR]) bieten Potenziale, die Diagnostik und Behandlung in der Psychotherapie zu verbessern. KI-gesteuerte Technologien ermöglichen die präzise Analyse großer Datensätze zur Erkennung von Mustern und zur genauen Vorhersage und bietet z. B. im Kontext der Diagnose von Depressionen vielversprechende Einsatzmöglichkeiten. Extended-Reality-(XR)-Technologien wie Virtual Reality (VR) und Augmented Reality (AR) bieten immersive und interaktive Umgebungen, die sowohl in therapeutischen Interventionen als auch in der Diagnostik genutzt werden können. Dieser Überblick hebt das Potenzial von KI und XR in der klinischen Psychologie hervor und beschreibt ihre Vorteile, darunter eine erhöhte Diagnosegenauigkeit und Standardisierung, frühzeitige Erkennung und verbesserte Effizienz. Es werden auch die Einschränkungen und Herausforderungen ihres Einsatzes in der klinisch-psychologischen Praxis behandelt. Darüber hinaus werden ethische Überlegungen und regulatorische Rahmenbedingungen diskutiert, wobei der Fokus auf den neuesten EU-Vorschriften zur KI und deren Auswirkungen auf die klinische Praxis liegt. Zukünftige Trends und Entwicklungen werden ebenfalls beleuchtet.
Objectives: Content-based access (CBA) to medical image archives, i.e. data retrieval by means of image-based numerical features computed automatically, has capabilities to improve diagnostics, research and education. In this study, the applicability of CBA methods in dentomaxillofacial radiology is evaluated.
Methods: Recent research has discovered numerical features that were successfully applied for an automatic categorization of radiographs. In our experiments, oral and maxillofacial radiographs were obtained from the day-to-day routine of a university hospital and labelled by an experienced dental radiologist regarding the technique and direction of imaging, as well as the displayed anatomy and biosystem. In total, 2000 radiographs of 71 classes with at least 10 samples per class were analysed. A combination of co-occurrence-based texture features and correlation-based similarity measures was used in leaving-one-out experiments for automatic classification. The impact of automatic detection and separation of multi-field images and automatic separability of biosystems were analysed.
Results: Automatic categorization yielded error rates of 23.20%, 7.95% and 4.40% with respect to a correct match within the first, fifth and tenth best returns. These figures improved to 23.05%, 7.00%, 4.20%, and 20.05%, 5.65% and 3.25% if automatic decomposition was applied and the classifier was optimized to the dentomaxillofacial imagery, respectively. The dentulous and implant systems were difficult to distinguish. Experiments on non-dental radiographs (10 000 images of 57 classes) yielded 12.6%, 5.6% and 3.6%.
Conclusion: Using the same numerical features as in medical radiology, oral and maxillofacial radiographs can be reliably indexed by global texture features for CBA and data mining.