This article investigates the phenomenon of rebound effects in relation to a transition to a Circular Economy (CE) through qualitative inquiry. The aim is to gain insights in manifestations of rebound effects by studying the Dutch textile industry as it transitions to a circular system, and to develop appropriate mitigation strategies that can be applied to ensure an effective transition. The rebound effect, known originally from the energy efficiency literature, occurs when improvements in efficiency or other technological innovations fail to deliver on their environmental promise due to (behavioral) economic mechanisms. The presence of rebound in CE contexts can therefore lead to the structural overstatement of environmental benefits of certain innovations, which can influence reaching emission targets and the preference order of recycling. In this research, the CE rebound effect is investigated in the Dutch textile industry, which is identified as being vulnerable to rebound, yet with a positive potential to avoid it. The main findings include the very low awareness of this effect amongst key stakeholders, and the identification of specific and general instances of rebound effects in the investigated industry. In addition, the relation of these effects to Circular Business Models and CE strategies are investigated, and placed in a larger context in order to gain a more comprehensive understanding about the place and role of this effect in the transition. This concerns the necessity for a new approach to how design has been practiced traditionally, and the need to place transitional developments in a systems perspective. Propositions that serve as theory-building blocks are put forward and include suggestions for further research and recommendations about dealing with rebound effects and shaping an eco-effective transition. Thomas Siderius, Kim Poldner, Reconsidering the Circular Economy Rebound effect: Propositions from a case study of the Dutch Circular Textile Valley, Journal of Cleaner Production, Volume 293, 2021, 125996, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2021.125996.
In this dissertation Maarten ter Huurne investigates why users in the sharing economy trust each other.
This chapter discusses the sharing economy in the Netherlands, focussing on shared mobility and gig work platforms. The Netherlands has been known as one of the pioneers in the sharing economy. Local initiatives emerged at the beginning of the 2010s. International players such as Uber, UberPop, and Airbnb followed soon after. Initially, the sharing economy was greeted with a sense of optimism, as it was thought to contribute to social cohesion and sustainability. Over the last few years, the debate has shifted to the question of how public values can be safeguarded or stimulated. In this regard, shared mobility is hoped to contribute to more sustainable transport. In the gig economy, scholars and labour representatives fear a further flexibilisation of labour; others see opportunities for economic growth.
The transition towards an economy of wellbeing is complex, systemic, dynamic and uncertain. Individuals and organizations struggle to connect with and embrace their changing context. They need to create a mindset for the emergence of a culture of economic well-being. This requires a paradigm shift in the way reality is constructed. This emergence begins with the mindset of each individual, starting bottom-up. A mindset of economic well-being is built using agency, freedom, and responsibility to understand personal values, the multi-identity self, the mental models, and the individual context. A culture is created by waving individual mindsets together and allowing shared values, and new stories for their joint context to emerge. It is from this place of connection with the self and the other, that individuals' intrinsic motivation to act is found to engage in the transitions towards an economy of well-being. This project explores this theoretical framework further. Businesses play a key role in the transition toward an economy of well-being; they are instrumental in generating multiple types of value and redefining growth. They are key in the creation of the resilient world needed to respond to the complex and uncertain of our era. Varta-Valorisatielab, De-Kleine-Aarde, and Het Groene Brein are frontrunner organizations that understand their impact and influence. They are making bold strategic choices to lead their organizations towards an economy of well-being. Unfortunately, they often experience resistance from stakeholders. To address this resistance, the consortium in the proposal seeks to answer the research question: How can individuals who connect with their multi-identity-self, (via personal values, mental models, and personal context) develop a mindset of well-being that enables them to better connect with their stakeholders (the other) and together address the transitional needs of their collective context for the emergence of a culture of the economy of wellbeing?
Onze huidige voedselvoorziening wordt gekenmerkt door overmatig gebruik van bestrijdingsmiddelen zoals antibiotica, genetische manipulatie, overdadig veel transport, water en andere grondstoffen worden gebruikt en productieprocessen gebaseerd op fossiele brandstoffen. Ook wordt veel landbouwgrond dusdanig uitgeput dat de kwaliteit van de grond en de diversiteit sterk achteruit gaan. Gezonde en duurzaam geproduceerde voeding zou voor iedereen bereikbaar moeten zijn. Bovendien is er veel leegstand in verschillende regio’s, deze leegstand kan door middel van aquacultuur systemen zeer waardevol worden benut. Dit is de aanleiding geweest om te zoeken naar alternatieve mogelijkheden voor duurzame productie van voedsel binnen de agrifoodsector. Geïntegreerde aquacultuur systemen worden verwacht goed toepasbaar te zijn voor duurzame voedingsproductie. Deze systemen verminderen de afhankelijkheid van de huidige voedselvoorziening van chemie, olie en gas. Bovendien stimuleert het de lokale en regionale economie en schept het duurzame werkgelegenheid. De doelstelling is het sluiten van de materiaalstroomketen, het voorkomen van afvalstoffen en het stimuleren van grondstof besparing. De aanpak van dit project is daarom gericht op de transitie naar circulaire materiaalstromen waarbij hoogwaardig hergebruik van de materialen mogelijk is op een manier waarbij waarde wordt toegevoegd. Hierbij worden mogelijkheden verkent in het kader van de biobased economy en nieuwe business- en verdienmodellen van dergelijke geïntegreerde aquaculturen. De onderzoeksvraag voor A2FISH is welke circulaire business- en verdienmodellen er realiseerbaar zijn voor kansrijke geïntegreerde aquacultuursystemen binnen de agrifoodsector. Om die onderzoeksvraag uiteindelijk te kunnen beantwoorden, zijn een aantal deelvragen geformuleerd: • Welke aquacultuursystemen zijn kansrijk toepasbaar binnen de agrifoodsector? • Aan welke technische en economische aspecten moet een aquacultuursysteem voldoen om te komen tot kansrijke business- en verdienmodellen? • Welke soorten planten kunnen worden met waardevolle inhoudsstoffen kunnen worden gekweekt met de aquacultuursystemen? • Welke soorten gangbaar industrieel visvoer kan worden gefabriceerd uit reststromen uit de voedingsmiddelenindustrie en welke invloed heeft dit voer als bemesting op de waterkwaliteit? • Hoe ziet een vervolgtraject voor een geïntegreerd circulair aquacultuursysteem eruit en in hoeverre is dit anders dan voor gangbare alternatieven?
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
