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Record W4406749965 · doi:10.1108/meq-05-2024-0183

Opportunities and challenges of strategic planning in the context of circular economy: an exploratory analysis

2025· article· en· W4406749965 on OpenAlexaffabout
Aline Gabriela Ferrari, Daniel Jugend, Fabiano Armellini, Bruno Michel Roman Pais Seles

Bibliographic record

VenueManagement of Environmental Quality An International Journal · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCircular economyContext (archaeology)Exploratory analysisStrategic planningBusinessProcess managementEngineeringManagement scienceComputer scienceMarketingGeologyData scienceBiology

Abstract

fetched live from OpenAlex

Purpose This study aims to explore relationships between strategic planning and the adoption of the circular economy (CE), addressing a gap in current research about the role strategic planning plays in supporting the implementation of CE. Design/methodology/approach To achieve the objective of this research, case studies were conducted at four Canadian companies with well-established environmental sustainability strategies. Findings The findings highlight the importance of engaging both internal and external stakeholders in facilitating knowledge exchange, as it is essential for strategic planning in CE initiatives. Additionally, the commitment of companies to circularity principles and the use of formal strategic planning tools are identified as valuable assets in the integration process. The study also presents and analyzes the challenges of integrating CE into companies’ strategic planning. Originality/value This study contributes to the existing literature by shedding light on the interplay between strategic planning and CE adoption, offering insights into the complexities and opportunities involved in integrating CE principles into organizational strategies. A framework for the integration of CE into strategic planning is also proposed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.117
GPT teacher head0.300
Teacher spread0.183 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations2
Published2025
Admission routes2
Has abstractyes

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