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.
This report describes the Utrecht regio with regard to sustainability and circular business models.
This lessons learned report gives an overview of the output and results of the first phase of the REDUCES project. The introduction states the relevance of combining a policy approach with business model analysis, and defines the objectives. Next, an overview is given of circular economy good business practices in the regions involved. Examining these business practices helped to define the regional needs for circular economy policy. This business approach proved to be a solid base for developing regional circular economy action plans, the last chapter of this report.
The modern economy is largely data-driven and relies on the processing and sharing of data across organizations as a key contributor to its success. At the same time, the value, amount, and sensitivity of processed data is steadily increasing, making it a major target of cyber-attacks. A large fraction of the many reported data breaches happened in the healthcare sector, mostly affecting privacy-sensitive data such as medical records and other patient data. This puts data security technologies as a priority item on the agenda of many healthcare organizations, such as of the Dutch health insurance company Centraal Ziekenfonds (CZ). In particular when it comes to sharing data securely, practical data protection technologies are lacking as they mostly focus on securing the link between two organizations while being completely oblivious of what is happening with the data after sharing. For CZ, searchable encryption (SE) technologies that allow to share data in encrypted form, while enabling the private search on this encrypted data without the need to decrypt, are of particular interest. Unfortunately, existing efficient SE schemes completely leak the access pattern (= pattern of encrypted search results, e.g. identifiers of retrieved items) and the search pattern (= pattern of search queries, e.g. frequency of same queries), making them susceptible to leakage-abuse attacks that exploit this leakage to recover what has been queried for and/or (parts of) the shared data itself. The SHARE project will investigate ways to reduce the leakage in searchable encryption in order to mitigate the impact of leakage-abuse attacks while keeping the performance-level high enough for practical use. Concretely, we propose the construction of SE schemes that allow the leakage to be modeled as a statistic released on the queries and shared dataset in terms of ε-differential privacy, a well-established notion that informally says that, after observing the statistic, you learn approximately (determined by the ε-parameter) the same amount of information about an individual data item or query as if the item was not present in the dataset or the query has not been performed. Naturally, such an approach will produce false positives and negatives in the querying process, affecting the scheme’s performance. By calibrating the ε-parameter, we can achieve various leakage-performance trade-offs tailored to the needs of specific applications. SHARE will explore the idea of differentially-private leakage on different parts of SE with different search capabilities, starting with exact-keyword-match SE schemes with differentially-private leakage on the access pattern only, up to schemes with differentially-private leakage on the access and search pattern as well as on the shared dataset itself, allowing for more expressive query types like fuzzy match, range, or substring queries. SHARE comes with an attack lab in which we investigate existing and new types of leakage-abuse attacks to assess the mitigation-potential of our proposed combination of differential privacy with cryptographic guarantees in searchable encryption. To stimulate commercial exploitation of SHARE-results, our consortium partners CZ and TNO will take the lead on applying and evaluating our envisioned technologies in various healthcare use-cases.
