MétaCan
Menu
Back to cohort

More Sustainable Supply Chains

2020· book-chapter· en· W3093452529 on OpenAlexaff
Robert D. Klassen, Jury Gualandris, William Diebel

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsWestern University
Fundersnot available
KeywordsSupply chainStructuringVariety (cybernetics)BusinessSustainabilityOpenness to experienceStakeholderCorporate governanceResource (disambiguation)Stakeholder engagementKnowledge managementProcess managementMarketingComputer scienceEconomicsManagementPolitical sciencePublic relations

Abstract

fetched live from OpenAlex

Abstract Management efforts to design, develop, and operate more sustainable supply chains encompass an increasingly complex variety of social and environmental issues. More sustainable supply chains must now consider how product, operations, natural resources, technologies, and multiple tiers of organizations collectively create value for a diverse set of stakeholders. For multiple reasons, research and practice have tended to adopt an outcome-based perspective, whereby these efforts focus on a sustainability “destination,” which suffers from several shortcomings. Drawing from research in operations management, stakeholder theory, institutional theory, and innovation, this chapter posits how more sustainable supply chains might be co-defined and co-developed by emphasizing a journey that engages multiple stakeholders beyond supply chain partners. Design thinking is a very promising approach, with its iterative steps of empathy, defining the problem, ideate, prototype, and test. This journey-based perspective provides a framework for structuring engagement and encouraging openness to new observations and insights. Finally, the breadth and depth of collaboration with stakeholders, the nature of governance mechanisms, and the form and scale of resource investment all provide the means to assess the journey as it occurs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.931
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.015
GPT teacher head0.180
Teacher spread0.165 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicSustainable Supply Chain ManagementFrench-language works237,207