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Business models towards circular economy: a bibliometric analysis

Business models towards circular economy: a bibliometric analysis

Correggi, Cecilia, Ghinoi, Stefano ORCID: 0000-0002-9857-4736 and Di Toma, Paolo (2022) Business models towards circular economy: a bibliometric analysis. In: 6th European Conference on Social Networks, 12th to 16th September 2022, Networks and Urban Systems Centre at the University of Greenwich, London. (Unpublished)

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In the recent years, Circular Economy has become a key paradigm for pursuing environmental and economic development, and therefore it has gained importance in the society, the business sector, and the academia. Indeed, considering the environmental problems that characterize the 21st century, firms are aware that business as usual is not an option for a sustainable future (Bocken et al., 2014) and they need to rethink the way they generate and deliver value. These changes have been analysed in the literature under the Business Model lens (Zott and Amit, 2010) and more precisely Business Model Innovation (Chesbrough, 2010). Moreover, a growing debate has focused on the role of dynamic capabilities in driving the process of Business Model Innovation towards Circular Economy. Several studies analysing Circular Economy and Business Modelling jointly have been carried out to date, and an analysis of the evolution of the debate, its sources, and current trends can help to understand the “state of the art” of the literature and the paths that still need to be taken. More precisely, considering that during the last few years the topic has seen an exponential increase of publications, an updated literature review is nowadays necessary. By using a bibliometric approach, this paper aims to address this need. Our analysis explores a large volume of scientific publications and uses bibliometric techniques to map the cumulative scientific knowledge (Donthu et al., 2021) on how Dynamic Capabilities foster the process of Business Model Innovation towards Circular Economy. Bibliometric analysis has the potential to show how specific disciplines, scientific domains, or research fields are conceptually, intellectually, and socially structured (Cobo et al., 2011) and, thus, it enables to identify knowledge gaps and potential avenues for future research. Following an approach similar to Goel and Jones (2016), we use a specific combination of keywords to identify all documents on family business and ambidexterity in Scopus, one of the primary scientific sources for bibliographic data (Singh et al., 2021). Our analysis concentrates on 1,057 documents and applies science mapping for visualising and analysing citation networks and co-occurrence networks: this approach is suitable for detecting relational patters and conceptual structures underlying the research field, hence adopting network analysis techniques for quantitatively assessing the role of specific individuals and concepts in the literature. Results show that key themes for practitioners and policymakers are emerging in the literature as well – for example, the impact of digitalisation and big data, Industry 4.0, and social sustainability – while motor themes referring to traditional theoretical approaches – such as the resource‐based view – continue to be central in the discussion but are re�enforced by specific links to novel elements, like the Sustainable Development Goals. These findings provide further advancements to previous works (e.g. Ferasso et al., 2020) on the evolution of the literature on circular business models.

Item Type: Conference or Conference Paper (Paper)
Uncontrolled Keywords: circular economy; bibliometric analysis; social network analysis; business model; dynamic capabilities
Subjects: H Social Sciences > HB Economic Theory
Faculty / School / Research Centre / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA)
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Last Modified: 03 Oct 2022 09:37

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