Implementing Industrial Symbiosis Incentives: an Applied Assessment Framework for Risk Mitigation
Authors
Azevedo, João
Vladimirova, Doroteya
Miller, Karen
Publication Date
2022-06Journal Title
Circular Economy and Sustainability
ISSN
2730-597X
Publisher
Springer Science and Business Media LLC
Volume
2
Issue
2
Pages
669-692
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Henriques, J. D., Azevedo, J., Dias, R., Estrela, M., Ascenço, C., Vladimirova, D., & Miller, K. (2022). Implementing Industrial Symbiosis Incentives: an Applied Assessment Framework for Risk Mitigation. Circular Economy and Sustainability, 2 (2), 669-692. https://doi.org/10.1007/s43615-021-00069-2
Abstract
<jats:title>Abstract</jats:title><jats:p>Industrial symbiosis (IS) is a business model that proposes symbiotic exchanges, allowing the flow of resources, wastes, and utilities between companies. In recent years, IS initiatives have been exponentially growing around the world. This can be attributed to the increasing awareness on the possibility of obtaining economic, environmental, and social benefits through the implementation of this model. Despite the exponential growth of IS initiatives, the companies are still facing problems in the achievement of reliable and permanent synergies. Over the years the literature has identified several factors in the IS emerging process. Incentives are among these factors, being defined as unlocking tools or mechanisms related to diverse dimensions such as economic, political, social, intermediaries, process, and technology. Authors believe that the large-scale implementation of IS incentives has not been properly addressed. In order to promote facilitated IS implementation and achieve a replicator effect, incentives should be fully addressed. In many case studies, it has been observed that the incentives for IS can be threatened by risks, compromising the implementation, and hindering the emerging process. This study developed a dedicated framework that is composed of incentive identification from best practices of IS and expert consultation; a risk assessment model based on risk factors identification and clustering; and finally, the mitigation actions based on the assessment outputs. The main result of this study is one set of mitigations actions that correlate the implementation levels (clusters) and the potential stakeholders involved.</jats:p>
Keywords
Behavioral and Social Science
Identifiers
s43615-021-00069-2, 69
External DOI: https://doi.org/10.1007/s43615-021-00069-2
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338481
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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