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Im Zeitalter der Machine Economy ist der maschinelle Dialog allgegenwärtig - das bietet neue Chancen für Nachhaltigkeit, erhöht gleichzeitig aber durch die zugrundeliegenden Technologien auch den Druck auf unsere Umwelt. Internet of Things (IoT), Künstliche Intelligenz (KI) und Distributed Ledger Technology (DLT) sind das technologische Fundament der Machine Economy. Damit verbunden sind Infrastrukturen, Datenströme und Anwendungen, die hohe Energie- sowie Ressourcenaufwände erzeugen. Der derzeitige politische Diskurs sowie die Nachhaltigkeitsforschung fokussieren sich auf Umweltwirkungen durch digitale Infrastrukturen. Daten, Applikationen sowie die Rolle von Akteuren als Treiber der Umweltwirkung werden zu wenig beleuchtet. In diesem Papier sprechen sich die Autorinnen und Autoren für eine "Grüne Governance der Machine Economy" aus. Adressiert werden Annahmen zu systemübergreifenden Treibern von Umweltbelastungen und ihrer Wirkung. Ziel ist es, ein Gesamtsystem nachhaltiger Entscheidungen und ein ökologisches Zusammenspiel aller beteiligten Technologien in der Wertschöpfung zu ermöglichen. Zukünftige Forschung soll die hier vorgestellten Hypothesen weiter ausarbeiten und konkrete Handlungsoptionen für eine Stakeholder übergreifende Roadmap erarbeiten.
Artificial intelligence in the sorting of municipal waste as an enabler of the circular economy
(2021)
The recently finalized research project "ZRR for municipal waste" aimed at testing and evaluating the automation of municipal waste sorting plants by supplementing or replacing manual sorting, with sorting by a robot with artificial intelligence (ZRR). The objectives were to increase the current recycling rates and the purity of the recovered materials; to collect additional materials from the current rejected flows; and to improve the working conditions of the workers, who could then concentrate on, among other things, the maintenance of the robots. Based on the empirical results of the project, this paper presents the main results of the training and operation of the robotic sorting system based on artificial intelligence, which, to our knowledge, is the first attempt at an application for the separation of bulky municipal solid waste (MSW) and an installation in a full-scale waste treatment plant. The key questions for the research project included (a) the design of test protocols to assess the quality of the sorting process and (b) the evaluation of the performance quality in the first six months of the training of the underlying artificial intelligence and its database.
Reuse is still seen as a "niche phenomenon" and consumers seem to waste economic opportunities linked to buying and selling second-hand products. For this reason, this paper focuses on incentives and barriers to sell and buy second-hand products, as indicated in the literature, and applies a theoretical framework of transaction costs to explain the existing consumption patterns. For this paper, a representative online survey was conducted in which 1023 consumers in Germany participated, age 16 and older. The data were analyzed for statistically significant deviations between different groups of economic actors selling or buying second-hand products. Results show that valuable unused products exist in households, but barriers such as uncertainties about the reliability of the buyer or the quality of the product hinder the transition into sustainable consumption. Different forms of transaction costs are important explanatory variables to explain why consumers nevertheless predominantly buy new products, although they are aware that second-hand would save money and make an individual contribution to climate protection.
The ultimate goal of German Resource Efficiency Programme (ProgRess) is to make the extraction and use of natural resources more sustainable and reduce associated environmental pollution as much as possible. By doing this - also with responsibility towards future generations - the programme should create a prerequisite for securing a long-term high quality of life. To bring the policy approaches formulated in ProgRess to reality, efforts to implement resource efficiency measures have to be increased at all levels - from international to regional to local.
The chapter intends to provide an impetus for the current debate on ProgRess policy development. The chapter identifies, analyses and describes deficits and possibilities of vertical integration of the German programme in particular and derives recommendations for action which may also serve as indications for other strategies. The following sections are based on results of the advisory report "Vertical integration of the national resource efficiency programme ProgRess (VertRess)", conducted by the German Institute of Urban Affairs (Difu) and the Wuppertal Institute for Climate, Environment and Energy on behalf of the German Environmental Agency (UBA) and the Federal Ministry of the Environment, Nature Conservation and Nuclear Safety (BMU).
With increasing world population and an unsettling resource scarcity in the back, sustainble consumption has moved to the foreground of political, economical and social discussions. One major school-of-thought is Circular Economy (CE), an approach summarizing various sustainable consumption activites under one roof. However, quantitative studies on the consumer are rare, yet crucial for a transfer from linear to circular consumption. This dissertation adds to literature by providing pioneer insights into consumer behavior in CE as an overarching concept, instead limiting research on singular subconcepts. Namely, four consumer activities are studied: recycling, upcycling, renting and sharing. In order to identify relevant insights for both academics and practitioners in CE, the research question ("what drives participation in CE?") is broken down into sub-hypotheses, which are addressed by three empirical studies. Using the SOR-Model (adaption Belk 1975) as overarching logic, the three studies deal with (1) the consumer (and their motivation) and situational stimuli (both (2) offline and (3) online). Respectively, three data sets are consulted to assess the sub-hypotheses and to identify overarching insights on how to accelerate consumer participation in CE, The research methodology employed ranges from a structured equation model (SEM), a random allocation field experiment during Fashion Week in Berlin to a discrete-choice model with best-worst scaling. The dissertation succeeds in revealing that (1) different activities in CE can be summarized in one latent variable, proving CE as a wholesome concept in consumer-related activities; that (2) Trust has a leveraging effect on participation in CE activities. Further, Trust can be enhanced offline via face-to-face interaction and online via third-party online attributes.; and that (3) experience in CE activities affects perception of online attributes, implying the need for adapted measures when dealing with CE-unexperienced consumers as compared to consumers with prior experience in CE activities.