Modeling Organizational Capabilities on a Strategic Level

Stirna, Jānis; Zdravković, Jelena; Henkel, Martin; Loucopoulos, Pericles; Stratigaki, Christina

doi:10.1007/978-3-319-48393-1_18

Cited by 1 publication

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ESymbiosis matching algorithm uses a similarity measure based on explicit and tacit knowledge [66]. In i-Symbiosis, the synergies are rejected if the relevance rate is lower than 60% [67]. Bakogianni et al (2019) [57] used matching rates indicating the level of compatibility between offered and requested material.…”

Section: State Of the Artmentioning

confidence: 99%

Circular Economy Matchmaking Framework for Future Marketplace Deployment

Łȩkawska-Andrinopoulou

Tsimiklis

Leick

et al. 2021

Sustainability

View full text Add to dashboard Cite

Online marketplaces enable cooperation between potential stakeholders by supporting offer and demand identification at the secondary raw material markets. The use of marketplaces facilitates communication between supply chain actors operating within the same or different industry sectors and enables detection of ways to close the loop of their products. This research investigated which criteria to use for the circular cooperation matching of companies in the context of a marketplace. These criteria were used for the development of a circular economy (CE) matchmaking framework based on a multi-level approach and relevance scoring between the users. The multi-level approach is based on the following criteria: (i) the compliance with circular economy principles, (ii) the material flows analysis, (iii) the greenhouse gas (GHG) emissions from transport. Based on those aspects a Total Relevance Score (TRS) between the stakeholders is calculated. The Total Relevance Score indicates the possibility for successful circular cooperation between two partners who are willing to close their loops with the best possible match. The logic behind the proposed circular economy matchmaking framework is illustrated by four cases using data collected from companies. Recommendations for further deployment are proposed. The developed framework, by incorporating circular economy principles for the first time within the matching algorithm, provides the opportunity for interested stakeholders for more tailored matching and increases their possibilities of finding a perfect match on the secondary raw materials market in terms of circularity. A similar approach has not yet been reported in the literature. The circular economy matchmaking framework constitutes a theoretical basis of an online marketplace to be developed.

show abstract