Dynamics of Business Models in Industry-wide Collaborative Networks for Circularity

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Date
2022-01-04
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Mark
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MDPI
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Abstract
Incumbent B2B manufacturing companies join forces and form collaborative networks, called consortia, aiming to increase the circularity of their products. Our research interest lies in the understanding of how the business models (BM) of the companies and the industry are affected by such collaborations in the collaborative networks of the circular economy (CE). Given the exploratory nature of our empirical research, we applied a mixed research strategy of an inductively deductive nature. We carried out case studies in a manufacturing industry field and combined them with quantitative content analyses of the companies’ financial and non-financial reports. Drawing on the assumptions of the Attention-Based View Theory and Legitimacy Theory, we defined and found verbally communicated identifiers of BM elements, CE strategies, and collaborative networks, quantified their occurrences, and transformed them into variables. Using correlation analyses, we determined the tightness and the changes in relationships between the BMs’ elements and CE strategies. We examined the dynamic changes in the structure of BMs and their elements occurring within the implementation of selected CE strategies. Our findings suggest that collaborative networks for CE support an adaptation of the industry’s BMs. The higher-level CE strategies impact the BM more than the lower-level ones. The contribution of our research is in the suggested method of quantification and concretization of an abstract concept of BMs’ elements and their interrelations. This enables an assessment and a direct comparison of BMs, as well as of implemented CE strategies across companies and across industries. Our results also shed more light on the way the companies and industries adapt their BMs towards reaching circularity, as well as on how collaborative networks support such a transition.
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Journal of Open Innovation, Technology, Market, and Complexity. 2022, vol. 8, issue 1, p. 1-24.
https://www.mdpi.com/2199-8531/8/1/3
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Peer-reviewed
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en
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Creative Commons Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
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