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Record W4415836418 · doi:10.1002/bse.70299

An Integrative Model for Resilience Through Circular Business Models: Insights Using a Multilevel Perspective

2025· article· en· W4415836418 on OpenAlexaff
Stéphane Jedrzejczak, Liliane Carmagnac, Minelle E. Silva, Benyamin Aghhavani-Shajari, Jesús González-Feliu

Bibliographic record

VenueBusiness Strategy and the Environment · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Manitoba
FundersAgence Nationale de la Recherche
KeywordsResilience (materials science)Perspective (graphical)SustainabilityContext (archaeology)Value (mathematics)InterviewCircular economy

Abstract

fetched live from OpenAlex

ABSTRACT This study investigates how circular business models (CBMs) can lead to resilience. Despite the increasing number of CBM studies, they have not fully addressed the need for resilience. As such, we employ a multilevel perspective to reveal the existing and potential relationships between CBMs and resilience under the sustainability umbrella. A two‐stage methodological approach was adopted by reviewing 125 published studies to unpack the way these constructs are interconnected, and interviewing experts to have an up‐to‐date perspective about CBMs and resilience. Data were analyzed using content analysis and organized through the CBM canvas to illustrate our results on value creation, proposition, delivery, capture, and resilience capabilities. The findings show that scholars often focus on narrow elements of environmental or economic sustainability and neglect the effective impact of circularity in various contexts. In parallel, experts reinforce how CBMs are context dependent and must urgently tackle climate change. An integrative model based on our analysis was developed to represent how CBMs can be aligned with resilience across multiple levels. This model extends our theoretical understanding of ways to fit resilience into CBMs and can help practitioners identify pathways for moving forward to achieve a circular economy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.253
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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