| Title | Risk assessment for circular business models: A fuzzy Delphi study application for composite materials |
|---|---|
| ID_Doc | 21629 |
| Authors | Tuni, A; Ijomah, WL; Gutteridge, F; Mirpourian, M; Pfeifer, S; Copani, G |
| Title | Risk assessment for circular business models: A fuzzy Delphi study application for composite materials |
| Year | 2023 |
| Published | |
| Abstract | Circular economy (CE) implementation requires the transition from linear business models (BMs) to circular ones, with related uncertainties and multi-disciplinary risks, which often discourage organisations. However, there is still a lack of understanding of risks associated with this process. This work thus aims to identify, classify and prioritise key risk factors for innovative circular BMs in order to enable the development of appropriate risk management strategies. A fuzzy Delphi method was tailored to assess the risk factors obtained from the literature and was applied to the industrial case of composite materials. 24 major risk factors for innovative circular BMs were identified and classified into six categories. The probability and impact of the risk factors were evaluated by experts and the risk factors were then ranked by calculating their risk scores. The resultant major risks appeared to be related to the external context in which organisations operate. Among those risks, the greatest were those generated by take back systems and low customers' acceptance of CE products. This research is the first to address risks for circularity in a structured way and contributes to the field of CE by providing an extensive list and classification of risk factors for innovative circular BMs as they are perceived by industry, acting as a reference for academics and practitioners. Furthermore, it provides the first evaluation and prioritisation of risk factors within the CE domain, highlighting critical risks within the specific industrial context of composite materials and suggesting action priorities for the establishment of circular BMs. |
| https://doi.org/10.1016/j.jclepro.2022.135722 |
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