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Record W2325107314 · doi:10.1016/j.jom.2016.03.002

Professional service supply chains⋆

2016· article· en· W2325107314 on OpenAlexaff
Jean Harvey

Bibliographic record

VenueJournal of Operations Management · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsConceptualizationPerspective (graphical)Service (business)Set (abstract data type)Dual (grammatical number)Supply chainComputer scienceProduct (mathematics)SociologyService providerService systemReflection (computer programming)Knowledge managementBusinessPublic relationsMarketingPolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Professional service (PS) exchanges are seldom narrowly bounded in time and space. This conceptual paper discusses prolonged PS sequences involving different professionals and different types of professionals. It is framed by the dual concepts of service episodes, representing the client's perspective and experience, and PS supply chains, that is, organized sequences of professional, clerical, and technical services explicitly set up to provide specific results, such as producing a financial product, designing a house, or replacing a hip. Four illustrative, empirically inspired situations are used to characterize episodes and supply chains. Each exemplar, two each from the health and social work sectors, is real and draws on publicly available data. The richness of the public information is a reflection of the fact that each is some form of failure or “disaster” (Altay and Ramirez, 2010). This dual conceptualization leads to a holistic perspective obtained by using the complex adaptive systems framework (Dooley and Van de ven, 1999, Levin, 1998) as a lens. The paper concludes with a discussion of the dynamics of such service systems and some proposals for a research agenda.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0030.005
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0390.002

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 head0.018
GPT teacher head0.245
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations41
Published2016
Admission routes1
Has abstractyes

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