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Record W2970627471 · doi:10.1108/ijmpb-11-2018-0263

Conceptualizing project team momentum: a review of the sports literature

2019· review· en· W2970627471 on OpenAlexaff
Thibaut Coulon, Henri Barki, Guy Paré

Bibliographic record

VenueInternational Journal of Managing Projects in Business · 2019
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsHEC MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsConceptualizationConstruct (python library)OriginalityProject managementValue (mathematics)Management scienceSociologyKnowledge managementField (mathematics)PsychologyEngineering ethicsComputer scienceEngineeringQualitative researchSocial scienceSystems engineering

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to develop a clear and generalizable conceptualization of project team momentum, as well as a detailed and engaging research agenda on this concept. Design/methodology/approach A literature review was conducted to achieve the study’s objectives. The review acknowledges the meanings that researchers in the field of sports have ascribed to the concept of momentum. Findings The paper develops a multidimensional (cognitive, affective and behavioral) conceptualization of project team momentum, as well as a conceptual framework that clearly distinguishes this construct from its antecedents and consequences. Research limitations/implications The paper encourages researchers to adopt the proposed conceptualization of project team momentum and to investigate the questions proposed in the research agenda. Originality/value The paper develops a strong conceptual basis for a concept that is highly relevant to, but currently not well-understood in, the project management domain. The proposed conceptualization is likely to contribute to the development of a sound theory of project team dynamics and project success.

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)0.007
metaresearch head score (Gemma)0.018
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: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.011
Science and technology studies0.0010.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.078
GPT teacher head0.327
Teacher spread0.249 · 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
GenreReview

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

Citations3
Published2019
Admission routes1
Has abstractyes

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