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Record W2910694652 · doi:10.3390/su11020390

Assessing the Potential of Sustainable Value Chains in the Collaborative Economy

2019· article· en· W2910694652 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainability · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsMcGill UniversityHEC MontréalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsArchetypeSustainabilitySustainable ValueValue chainSharing economyIndustrial organizationBusiness modelValue (mathematics)BusinessMarketingCircular economyProfit (economics)EconomicsKnowledge managementMicroeconomicsSupply chainComputer science

Abstract

fetched live from OpenAlex

The current business paradigm entails a narrow, profit-centered and managerially-focused nature. This article proposes that the study of the collaborative economy necessitates an inevitable shift in the conventional business paradigm and suggests that the institutional school of marketing thought, in general, and the electric theory of marketing, in particular, offers a useful theoretical framework for investigating the theoretical impact of the collaborative economy on the value chain. Uber is used as an illustrative case, on which the electric theory of marketing is applied, to demonstrate how the archetype of the collaborative economy theoretically impacts the value chain and contributes to sustainability in the value chain in the transportation services industry. The study provides further insights in the form of suggestions and propositions for ensuring sustainability in the value chain of collaborative systems.

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.

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)0.003
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 score0.427
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.007
GPT teacher head0.244
Teacher spread0.236 · 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