MétaCan
Menu
Back to cohort

Not For-Profit Focal Firms in Supply Chain Management: Future Research Directions

2018· article· en· W2823168805 on OpenAlexaboutno aff
Kevin Dooley, Jury Gualandris, David G. Hyatt, Jonathan L. Johnson, Robert D. Klassen, Annachiara Longoni, Davide Luzzini, Mark Pagell

Bibliographic record

VenueAcademy of Management Proceedings · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexSupply chainBusinessProfit (economics)ManagementMarketingEconomicsFinance

Abstract

fetched live from OpenAlex

This symposium examines supply chain management strategy, practices and structures adopted by focal actors in the network not motivated primarily by profit. The potential focal actors might include: NGOs, social ventures, B-corporations and other organizations for whom profitability matters but it is not the primary goal as well as regulators and other governmental actors, co-ops and other collectives, communities and natural systems where for-profit ventures operate. The main aim of this symposium is to discuss whether these organizations enact unique or presently unknown strategies and practices to achieve their goals or adopt traditional supply chain management approaches. Configuring Supply Networks for International Non-governmental Organizations Presenter: Jury Gualandris; Ivey Business School Presenter: Robert D Klassen; U. of Western Ontario Social Impact Supply Chain Management Presenter: Madeleine Pullman; Portland State U. Presenter: Annachiara Longoni; ESADE Business School Presenter: Davide Luzzini; EADA Business School The Role of Social Capital in Cross-Sector Supply Chains Presenter: Jonathan Johnson; U. of Arkansas Presenter: Kevin Dooley; Arizona State U. Presenter: David Graham Hyatt; U. of Arkansas

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.039
GPT teacher head0.302
Teacher spread0.263 · 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
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAcademy of Management ProceedingsSame topicOutsourcing and Supply Chain ManagementFrench-language works237,207